Stroke face dataset The sources of their dataset were Stroke Faces on Kaggle, YouTube-Facial-Palsy-Database, and Yale Face Database. It was introduced in our paper Fake It Till You Make It: Face analysis in the wild using synthetic data alone. Each observation corresponds to one patient, and the attributes are variables about the health status of each patient. Check for signs of a stroke. In this model, the goal is to create a deep learning application that identifies brain strokes using a convolution neural network. , stroke, amyotrophic lateral sclerosis (ALS), Parkinson’s disease (PD), etc. Abdominal and Direct Fetal ECG Database: Multichannel fetal electrocardiogram recordings obtained from 5 different women in labor, between 38 and 41 weeks of gestation. Computerized assessments of expressions based on facial symmetry obtained from images of the face have been developed, which were trained using a generic dataset of healthy individuals’ facial videos because the stroke dataset is small. AutoTrain Dataset for project: stroke-classifier Dataset Description This dataset has been automatically processed by AutoTrain for project stroke-classifier. DARK FACE dataset provides 6,000 real-world low light images captured during the nighttime, at teaching buildings, streets, bridges, overpasses, parks etc. 291 images 1 model. The dataset underwent Involuntary Eye Movements during Face Perception: Dataset 1, 26 electrodes, 500Hz sampling rate, and 120 trials. 22M images of 110K unique identities. This aims There are two main processes of stroke faces and normal faces classification, the first is training and the second one is testing. stroke_face (v5, 2023-12-27 4:22pm), created by project-ieywg This study analyzed a dataset comprising 663 records from patients hospitalized at Hazrat Rasool Akram Hospital in Tehran, Iran, including 401 healthy individuals and 262 stroke patients. and ambulance staff using the face arm speech test. 5E. Number of currently avaliable datasets: 95 Number of subjects across all datasets: 3372. To achieve that was created a special model, using Active appearance model (AAM) algorithm that detected cheek wrinkle line by training face dataset. stroke_face (v4, 2023-12-22 10:15am), created by project-ieywg The Stroke Prediction Dataset provides essential data that can be utilized to predict stroke risk, improve healthcare outcomes, and foster research in cardiovascular health. and get access to the augmented documentation experience Collaborate on models, datasets and Spaces Sign Up. (2) Ensuring the relevance of text to facial images requires the use of natural We’re on a journey to advance and democratize artificial intelligence through open source and open science. The results may improve if the models of Py-feat are fine-tuned with the stroke dataset. However, many methods developed Index Terms—Algorithmic bias, dataset, face alignment, oro-facial impairment, amyotrophic lateral sclerosis, stroke. n=655), test (masks hidden, n=300), and generalizability (completely hidden, n=316) data. The key to diagnosis consists in localizing and delineating brain lesions. AI-generated faces in real time. 11 Cite This Page : This study emphasizes the importance of comprehensive datasets comprising both stroke and non-stroke faces of individuals for effective model training. However, analyzing large rehabilitation-related datasets is Discover high-resolution human face datasets for face recognition, detection, and segmentation models’ training. • Wepre-trainourmodelusing6,655frontalfacephotos collected from ten face datasets, and construct an AP-Drawing dataset (containing 140 high-resolution face According to clinical reports, people with ages between 60 to 79 years have a high risk of stroke. Tasks: Text Classification. 16 and 85. building face mountain object plant road sidewalk sign tree window biped flower-box flower-pot furniture sea sky stairs stroke syt. CMU PIE 人脸库建立于2000年11月，它包括来自68个人的40000张照片，其中包括了每个人的13种姿态条件，43种光照条件和4种表情下的照片，现有的多姿态人脸识别的 FaceScape provides large-scale high-quality 3D face datasets, parametric models, docs and toolkits about 3D face related technology. ; A Comprehensive Dataset of Pattern Electroretinograms for Ocular Electrophysiology Research: The PERG-IOBA Dataset: 336 CSV records with 1354 PERG Overall, compared to other diseases such as Alzheimer's disease, there is a relative paucity of large, high-quality datasets within stroke. The main symptoms of a stroke can happen suddenly. , stroke, amyotrophic lateral sclerosis (ALS), Parkinson’s disease (PD), Introduction: Facial droop (FD) is a common symptom (45-60%) of stroke so early detection is critical for timely treatment. Images are downloaded from Google Image Search and have large Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. StrokeRehab consists of high-quality inertial measurement unit sensor and video data of 51 stroke-impaired patients and 20 healthy subjects A Chinese woman playing badminton, on a green court, holding the racket in her right hand, forehand overhead stroke, drive shot, black and red racket, white handle, white shuttlecock in the air to the left of the player, red T-shirt, blue shorts, black and yellow sneakers, whole body, side view, photo-realistic, Yonex and HSBC banners in the blurry background. like 0. The eyelids, cheeks, and corners of the mouth may appear pulled down, and the person may have difficulty smiling voluntarily or speaking clearly. Standard stroke examination protocols include the initial evaluation from a non-contrast CT scan to discriminate between hemorrhage and ischemia. Costs include the cost of health care services, medicines to treat stroke, and missed days of work. (NCKU) Robotics Face datasets. Dataset card Viewer Files Files and versions Community 1 Subset (1) default · 5. Generators. In this study, we proposed a facial stroke recognition system that assists patients in self-judgment. Hot. Immediate attention and diagnosis play a crucial role regarding patient prognosis. A regression imputation and a simple imputation are applied for the missing values in the stroke dataset, respectively. However, these synthesized edge maps strictly align with the edges of the corresponding face images, which limit their generalization ability to real hand-drawn sketches with vast Note that when accessing the image column: dataset[0]["image"] the image file is automatically decoded. The dataset aims to However, the clinical application of these technologies still faces challenges such as limitations in data volume, model interpretability, and the need for real-time monitoring and updating. Datasets are collections of data. The dataset consisted of 10 metrics for a total of 43,400 patients. Explore Popular Topics Like Government, Sports, Medicine, Fintech, Food, More. This large, diverse dataset can be used to train and test lesion segmentation algorithms and provides a standardized dataset for comparing the performance of different segmentation According to the WHO, Cerebrovascular Stroke (CS) is the second largest cause of death in the lower face, with a preservation of the upper face muscles. While using such data to Stroke is the leading cause of adult disability worldwide, with up to two-thirds of individuals experiencing long-term disabilities. Therefore, it is not enough to adjust the margin between classes for face recognition with mask bias. Chastity Benton 03/2022 [ ] spark Gemini keyboard_arrow_down Task: To create a model to determine if a patient is likely to get a stroke based on the parameters provided. This is 12) stroke: 1 if the patient had a stroke or 0 if not *Note: "Unknown" in smoking_status means that the information is unavailable for this patient. Here we present ATLAS Acute ischemic stroke dataset contains 397 Non-Contrast-enhanced CT (NCCT) scans of acute ischemic stroke with the interval from symptom onset to CT less than 24 hours. It contains all prompts extracted from images up to May 5th, 2024, the data was sourced from scratch using my own pipeline. This dataset is used to predict whether a patient is likely to get stroke based on the input parameters like gender, age, and various diseases and smoking status. Updated Oct 9, 2020; jian667 / face-dataset. Upload or create new data files. subdirectory_arrow_right 2 cells hidden spark Gemini 下载链接：VGG Face Dataset. Bed-based BCG Dataset: ref: 40: ECG, BCG, BP: Recordings from adults whilst at rest. However as soon as your Dataset has an indices mapping, the speed can become 10x slower. These docs will guide you through interacting with the datasets on the Hub, uploading new datasets, exploring the datasets contents, and using datasets in your projects. g. Flickr Faces: This high-quality image dataset features 70,000 high-quality PNG But in the masked face dataset, the mask data augmentation is oriented to all identities, i. NVIDIA 20. 52% respectively. The process has four stages: a pilot punching stage, a round stamping stage, deep drawing and a cut-out stage. To identify the stroke, they used Deep Learn ing methods . The remaining 38 unmatched samples were used as a part of the independent test dataset. This is because there is an extra step to get In this project, we will attempt to classify stroke patients using a dataset provided on Kaggle: Kaggle Stroke Dataset. Follow. The International Stroke Database is dedicated to providing the international stroke research community with access to clinical and research data to accelerate the development and application of advanced neuroinformatic techniques in We present the first public dataset with videos of oro-facial gestures performed by individuals with oro-facial impairment due to neurological disorders, such as amyotrophic lateral sclerosis (ALS) and stroke. MORPH is a dataset for estimating age from faces. The dataset consists of over 20,000 face images with annotations of age, gender, and ethnicity. , each class contains masked samples. jsonl file. The dataset consists of over $5000$ individuals and $10$ different input variables that we will use to predict the risk of stroke. stroke_face (v3, 2023-12-21 11:00am), created by project-ieywg A clean version (wash list) of MS-Celeb-1M face dataset, containing 6,464,018 face images of 94,682 celebrities. like 50. With the help of machine learning techniques, early detection of various stroke alerts is accessible, which can efficiently prevent or diminish the stroke. Here we present ATLAS (Anatomical Tracings of Lesions After Stroke), an open-source dataset of 304 T1-weighted MRIs with manually segmented lesions and metadata. Decoding of a large number of image files might take a significant amount of time. - GitHub - openlists/ElectrophysiologyData: A list of openly available datasets in (mostly human) electrophysiology. The dataset was randomly divided into five groups with balanced samples. StrokeRehab is a large-scale, multimodal dataset that serves as a new benchmark for recognizing elemental short-duration actions at high temporal resolution. We’re on a journey to advance and democratize artificial intelligence through open source and open science. Acknowledgements (Confidential Source) - Use only for educational We conducted extensive experiments on three public face datasets, whose results demonstrate that our network achieved a state-of-the-art improvement in all face categories in comparison with other popular segmentation models. Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. ATLAS: Anatomical Tracings of Lesions After StrokeQD is a large-scale ischemic stroke dataset established by the cooperation of VRIS research team in Qingdao University of Science & Technology，Qilu Hospital of Shandong University (Qingdao) and Qingdao Municipal Hospital. Open databases. 11 ATLAS is the largest dataset of its kind and Recently, efforts for creating large-scale stroke neuroimaging datasets across all time points since stroke onset have emerged and offer a promising approach to achieve a better understanding of The dataset used in this project contains two classes of images, with one class representing individuals who have been diagnosed with acute stroke and the other class representing individuals who After face alignment, all faces across the entire dataset are centered in the fixed-size image, scaled to an approximately identical size, and the eyes lie on a horizontal line. Thus it is important to first query the VGGFace2 Dataset for Face Recognition The dataset contains 3. 3M face images from over 9k different The dataset must consist of electroencephalography (EEG) data of 50-100 stroke patients. A stroke is a brain attack that occurs when blood flow is cut off to a part of the brain, subsequently resulting in the death of brain cells [2], [3]. 11 clinical features for predicting stroke events Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. SNIPR is based on the We’re on a journey to advance and democratize artificial intelligence through open source and open science. org is a project dedicated to the free and open sharing of. Stroke Prediction Module. For the offline processing unit, the EEG data are extracted from The “healthcare-dataset-stroke-data” is a stroke prediction dataset from Kaggle that contains 5110 observations (rows) with 12 attributes (columns). Using a deep learning model on a brain disease dataset, this method of predicting analytical techniques for stroke was carried out. To deal with drifting, many tracking methods require a failure detection and reinitialization method as a backup [31]. The system prototype The RGB videos from the Toronto Neuroface Dataset, which were recorded during standard orofacial examinations of 14 people with post-stroke (PS) and 11 healthy controls (HC) were used in this study. Learn more. but having already lost a day to trying and tuning different models for this dataset, I will recommend using a random In this article, we suggest a new approach that automatically analyzes the degree of left and right symmetry of the cheek wrinkle lines and the movement of both arms in order to detect the symptom of the early stroke. It contains 1. However, analyzing large datasets is problematic due to barriers in accurate stroke lesion When detecting faces in face detection software, the difficulty of detecting small, scale, position, occlusion, blurring, and partially occluded faces in uncontrolled conditions is one of the Shuffling takes the list of indices [0:len(my_dataset)] and shuffles it to create an indices mapping. The Stroke Neuroimaging Phenotype Repository (SNIPR) was created as a stroke-focused medical imaging repository that could serve as a platform for this and other stroke-related research. Stroke. map() with Collection of 5. dataset face-recognition face-dataset face-database relabel. Large-scale neuroimaging studies have shown promise in identifying robust biomarkers (e. Sketch samples are sorted by their Navier Stokes Dataset of Isotropic Turbulence in a periodic box The dataset for tensor-to-tensor or trajectory-to-trajectory neural operators, generated from Navier-Stokes equations to model the isotropic turbulence [1] such that the Stroke Datasets. Something went wrong and this page crashed! If the issue During a stroke, the face can droop on one or both sides. To verify the performance of FER-PCVT, we collect and annotate a private dataset of stroke patients containing 1302 samples, which can be divided into 8 classes: painful, strained, tired, neutral, happy A list of openly available datasets in (mostly human) electrophysiology. 0000044170. 2018. The subacute stroke patients with dysarthria showed abnormalities in vowel production, as revealed by the array of acoustic measures, including aberrant speech The KUAH dataset provides real-world data from stroke patients as well as from normal controls, which makes the proposed method useful for practical clinical use, for example, to assist in the remote diagnosis of strokes. This large, diverse dataset can be used to train and test lesion Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. doi: 10. OpenfMRI. This large, diverse dataset can be used to train and test lesion segmentation algorithms and provides a standardized dataset for comparing the performance of different segmentation To this end, we introduce a large-scale, multimodal dataset, StrokeRehab, as a new action-recognition benchmark that includes elemental short-duration actions labeled at a high temporal resolution. and stroke. Facial landmarks were tracked by an ensemble of regression trees (ERT) method. Stroke is a leading cause of disability, and Magnetic Resonance Imaging (MRI) is routinely acquired for acute stroke management. The largest dataset available from Civitai. Number of downloads for the medical datasets. We believe that the dataset will be very helpful for analysing brain activation and designing decoding methods that are more applicable for acute stroke patients, which will greatly facilitate research in the field of motor imagery-BCI. 0% DALYs), with the bulk of the global stroke burden (86. Action units were computed using XGBoost which was trained using HC, and classified using regression analysis for each of the nine facial expressions. Given an image of a Chinese character, stroke extraction aims to The stroke height of the tool is 63 mm and the material feed per stroke is 60 mm. In a future study, we plan to apply our model to stroke face segmentation and identify changes in the facial Stroke Predictions Dataset. 3. In addition, three models for predicting the outcomes have been developed. MagFace introduces an adaptive mechanism to learn a well-structured within-class feature distribution by The automatic detection of stroke signs has been we proposed using cosine similarity between the left and right sides of the face as a part of features for classifying the stroke elderly patients from healthy elderly participants. 1038/sdata. 0% (95% confidence interval, 71. They may also experience an Problems Faced: Highly imbalanced dataset (95% non-stroke, 5% stroke), missing values, irrelevant features, and un-encoded categorical variables. 33%, 98. Eye movements and pupil diameter record, EEG and EOG data is present when subject is presented a This is the first open dataset to address left- and right-handed motor imagery in acute stroke patients. tracking medical datasets, with a focus on medical imaging - adalca/medical-datasets. 2% (95% confidence interval, The face datasets were provided by the face reserch group at CMU. Created by project-ieywg Open-Patients is an aggregated dataset of public patient notes from four open-source datasets of public patient notes. We introduced AI-Sketcher, a deep generative model for generating high-quality multiclass sketches. The World Health Organization (WHO) ranks stroke as the second most prevalent cause of death worldwide [2]. Thanks to recent advances, stroke treatments and survival rates have improved greatly The Olivetti faces dataset# This dataset contains a set of face images taken between April 1992 and April 1994 at AT&T Laboratories Cambridge. At each node, the algorithm traverses down to the next node/leaf by selecting the most informative risk factor 1using entropy-based Information gain or the Gini index. Download Open Datasets on 1000s of Projects + Share Projects on One Platform. PreProcessing Techniques: One-hot Encoding, feature selection, under-sampling, normalization using standard scaler, k-fold cross validation, and nullity encoding. 8–86. raw magnetic resonance imaging (MRI) datasets. Some limitations that have stymied the development of large, open-access stroke ods [38], we construct a dataset of faces with identical ge-ometry but varying appearances, generating corresponding colored stroke maps using bilateral filtering and semantic clustering algorithms. It has been trained on a dataset of 11 million images Constructing a large-scale and high-quality facial image-text dataset presents several challenges [86, 34, 32], mainly in three aspects: (1) Obtaining a high-quality facial image dataset comprising tens of millions of images while ensuring a natural distribution and precise alignment of face. 0 (N=1271), a larger dataset of T1w stroke MRIs and manually segmented lesion masks that includes training (public. K. 4k. Our study is to develop a machine learning (ML)/AI based tool Datasets Toronto NeuroFace Dataset. The patients may be Here we present ATLAS v2. We present a public dataset of 2,888 multimodal clinical MRIs of patients with acute and early subacute stroke, with manual lesion segmentation, and metadata. The input variables are both numerical and categorical and will be explained below. A large, open source dataset of stroke anatomical brain images and manual lesion segmentations. 6 images for each subject. To address these issues, we constructed a stroke-based sketch dataset, FaceX. <|im_end|>\n<|im_start|>reasoning\nLet's break down the problem step by Dataset Card for FairFace Dataset Summary FairFace is a face image dataset which is race balanced. For more details, please take a look at the Research Paper. Dataset loading utilities#. OpenNeuro is a free and open platform for sharing neuroimaging data. MORPH . The dataset has 44 hours of recorded training and labeled using 2700 (approx. In the first stage, a 3 mm hole is punched in the metal strip. 0 (n=955), a larger dataset of stroke T1-weighted MRIs and lesion masks that includes both training (public) and test (hidden) data. There are three main types of stroke [4]: Transient Ischemic Attack (TIA) [5], tracking medical datasets, with a focus on medical imaging - adalca/medical-datasets. The <|im_start|>user\nProve that the difference between two consecutive cubes cannot be divisible by 5, using the fact that the only possible remainders when a cube is divided by 5 are 0, 1, and -1. - Robin-WZQ/AGFD-20K Stroke is the second leading cause of mortality worldwide. Tufts Face Dataset is a comprehensive, large-scale face dataset that contains 7 image modalities: visible, near-infrared, thermal, computerized sketch, LYTRO, recorded video, and 3D images. Perceptual clinical scores from trained clinicians are provided as metadata. Languages The BCP-47 code for the dataset's language is unk. Given a stroke dataset with risk factors {𝑅1,𝑅2,} and a stroke class In this article, we suggest a new approach that automatically analyzes the degree of left and right symmetry of the cheek wrinkle lines and the movement of both arms in order to detect the symptom of the early stroke. ‹‹ previous 1 2 next ›› Displaying datasets 1 - 10 of 14 in total. It was introduced in our paper DigiFace-1M: 1 Million Digital Face Images for Face Recognition and can be used to train deep learning models State-of-the-art face recognition models are trained on millions of real human face images collected from the internet. Object Detection Model snap. 1 It has taken more than a year for us to recruit a large pool of patients in various stroke-related emergencies, and the cohort stroke cases from non-stroke cases, regardless of the stroke subtypes. The patients underwent diffusion-weighted MRI (DWI) within 24 1779 open source stroke_mouth images and annotations in multiple formats for training computer vision models. Stroke is the leading cause of adult disability worldwide, with up to two-thirds of individuals experiencing long-term disabilities. Generated Photos. By utilizing the YOLOv8 models, the study leverages their advanced architectural improvements to enhance real-time processing capabilities. MAAD-Face consists of over 3. It has the attack Giga Drain with the cost Tufts Face Dataset. and accuracy. Our dataset is unique, as compared to existing ones [7,10], because our sub- face pose can be assumed. Whether you’re working on machine learning models or health risk analysis, this dataset offers a rich set of features for developing innovative solutions. 1. Object Detection This paper introduces the use of facial image dataset containing neutral and smiling expressions to classify facial weakness which is a common sign of stroke. 0% of deaths and 89. stroke. Our “real facial image dataset Involuntary Eye Movements during Face Perception: Dataset 1, 26 electrodes, 500Hz sampling rate, and 120 trials. DigiFace-1M aims to tackle three major problems associated with such large-scale face recognition datasets. Over a year, fifteen million people worldwide Hugging Face. source dataset of stroke anatomical brain images and manual lesion segmentations At the acute stage, within the first 24h or so after stroke onset, clinicians face important, time-sensitive We introduce the CPAISD: Core-Penumbra Acute Ischemic Stroke Dataset, aimed at enhancing the early detection and segmentation of ischemic stroke using Non-Contrast Computed Tomography (NCCT) scans. THE Here we present ATLAS (Anatomical Tracings of Lesions After Stroke), an open-source dataset of 304 T1-weighted MRIs with manually segmented lesions and metadata. Hugging Face currently contains 20 datasets. The Hugging Face Hub is home to a growing collection of datasets that span a variety of domains and tasks. For further details check the project's GitHub repository or the Hugging Face dataset cards (taskmaster-1, taskmaster-2, taskmaster-3). OK, Got it. 3. For the training, we have used an 80% dataset, and during the Acute ischemic stroke dataset contains 397 Non-Contrast-enhanced CT (NCCT) scans of acute ischemic stroke with the interval from symptom onset to CT less than 24 hours. , measures of brain structure) of stroke recovery. The first part contains 720K images with 10K identities. ) hours of manual 1779 open source stroke_mouth images and annotations in multiple formats for training computer vision models. Something went wrong The dataset is publicly available, which contributes to increased competition in the development of artificial intelligence systems and their advancement and quality improvement. we demonstrated the presence of bias in the landmark localization accuracy of pretrained face alignment approaches in our can perform well on new data. Learn more Stroke Faces - GAN image generation experiment. Project Name Investigators Accession Number Project Summary Sample Size In the fusiform face area, a face-space coding model with sigmoidal ramp tuning provided a Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. to get started. Stroke is a leading dataset of stroke Tw MRIs and manually-segmented lesion masks (ATLAS v. Immediate treatment may minimize the long-term effects of a stroke and even prevent death. . Cerebral stroke, the second most substantial cause of death universally, has been a primary public health concern over the last few years. However, deep learning still faces many challenges for stroke diagnosis. Free for academic research. A stroke occurs when a blood vessel that carries oxygen and nutrients to the brain is either blocked by a clot or ruptures. A Generated Face Dataset: AGFD-20K. Dataset Structure Data Instances A sample from this dataset looks as follows: CelebA Dataset: This dataset from MMLAB was developed for non-commercial research purposes. A Stage 2 Pokemon Card of type Grass with the title Venusaur and 140 HP of rarity None evolved from Ivysaur from the set Pokemon Rumble. Use the Edit dataset card button to edit it. 31 million images of 9131 subjects (identities), with an average of 362. 2 dataset. The dataset used for stroke prediction is very imbalanced. Flexible Data Ingestion. We found it was 82% accurate, meaning it correctly identified a ML approaches were employed on various datasets for solving various stroke problems for a better healthcare system and further and outcome prediction. The clinical dataset for this study was acquired in the ERs of the Houston Methodist Hospital in Texas by the physicians and caregivers from the Eddy Scurlock Stroke Center at the Hospital under an IRB-approved study. FD is a part of almost all stroke scales. But is it really because they don’t exercise enough or eat too much sugar? you may still face charges if law enforcement believes you In total, 185 confirmed stroke patients were kept as the positive group, and 551 non-stroke or healthy people were matched as the control group (Figure S1a) to build a stroke face recognition program by deep neural networks. 0. For the video module network, we employ state-of-the-art fairness-aware face image pre-training, the FairFace (Karkkainen and Joo, 2021) ResNet-34 model that was pre-trained on a face image dataset that has evenly distributed race, age, and ethnicity attributes. Thus it is important to first query the sample index The inability to move the muscles of the face on one or both sides is known as facial paralysis, which may affect the ability of the patient to speak, blink, swallow saliva, eat, or communicate through natural facial expressions. Globally, 3% of the population are affected by subarachnoid hemorrhage with class labels (stroke and no stroke) are termed the leaf nodes. It contains 200,000+ celebrity images. Created by project-ieywg. INTRODUCTION M ANY neurological diseases – e. For our study, as stroke facial paralysis can affect one or both sides of the face, we selected points on the face to capture the mirror positions of symmetry, comprising both sides Only the final output layers and the discriminator module are fine-tuned. Piczak. Hemorrhagic stroke images which are correctly classified by AlexNet are 94. Perceptual clinical scores from trained Large neuroimaging datasets are increasingly being used to identify novel brain-behavior relationships in stroke rehabilitation research 1,2. stroke_face (v1, 2023-12-21 9:53am), created by project-ieywg 1779 open source stroke_mouth images plus a pre-trained stroke_face model and API. Manual annotation of facial landmarks is also provided for a subset of over 3300 frames. To evaluate the impact of the scale of the dataset (n_samples and n_features) while controlling the statistical properties of When autocomplete results are available use up and down arrows to review and enter to select. Star 264. There are a total of 180,142 patient descriptions from these four datasets. To achieve appearance editing, di-rectly encoding edited stroke maps into the latent space of the pre-trained facial NeRF generation model [5] leads to stroke dataset successfully. Subplots represent 10 categories: horse, shark, duck, bicycle, teapot and face of TU-Berlin dataset and 30s and 90s levels of artist A and artist E in Disney portrait dataset. Images Data for the Acute Stroke Prediction using Deep Learning Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. As described on the original website: Stroke is the basic element of Chinese character and stroke extraction has been an important and long-standing endeavor (Lee and Wu 1998). We also provide 9,000 unlabeled low-light images collected from the same setting. Dataset card Files Files and versions Community The dataset is currently empty. The validation and test sets consist of 234 chest X-rays from 200 patients and 668 chest X-rays from 500 patients, respectively. We tested the tool on a small dataset, using video recordings of 14 people who had experienced a stroke, and 11 healthy controls. Additional factors in prediction Using datasets such as those from the NCBI and NIH, I obtained a dataset of 700 vascular data points, which I split into 400 data points for training and Face-sketch pairs : APDrawing: CVPR 2019 : : ️ : Portrait-sketch paired : SKSF-A: EG 2024 : : ️ : Face-sketch pairs of seven styles sketch sketch-generation sketch-synthesis vector-sketch stroke-level sketch-dataset sketch-generation For new and up to date datasets please use openneuro. To achieve this, we have thoroughly reviewed existing literature on the subject and analyzed a substantial data set comprising stroke patients. For each item in the dataset, there are two attributes: tracking of a face’s bounding box [49], of the rigid trans-formation parameters of heads [31,55], or of facial fea-tures [38]. Gecko vision. Toronto NeuroFace Dataset is a public dataset with videos of oro-facial gestures performed by individuals with oro-facial impairment due to neurological disorders, such as amyotrophic lateral sclerosis (ALS) and stroke. e. Deploy a Model Explore these datasets, models, and more on Roboflow Dataset details. 0% prevalent strokes, and 143. 67%, and for ischemic stroke accuracy is 96%. cases) increased substantially (70. They may include: face weakness – one side of your face may droop (fall) and it might be hard to smile; arm weakness – you may not be able to fully lift both arms and keep them there because of weakness or numbness in 1 arm 7. Implementing a combination of statistical and machine The dataset is audio-visual, so is also useful for a number of other applications, for example – visual speech synthesis, speech separation, cross-modal transfer from face to voice or vice versa and training face recognition from video to complement existing face recognition datasets. 1779 open source stroke_mouth images and annotations in multiple formats for training computer vision models. 0% deaths from stroke, 102. A dataset of arm motion in healthy and post Here we present ATLAS (Anatomical Tracings of Lesions After Stroke), an open-source dataset of 304 T1-weighted MRIs with manually segmented lesions and metadata. Split (1) Stroke-related costs in the United States came to nearly $56. This large, diverse dataset can be 1779 open source stroke_mouth images plus a pre-trained stroke_face model and API. View Datasets; FAQs; Submit a new Dataset; Login; Datasets. Ethical The smartphone tool, which has an accuracy rating of 82% for detecting stroke, would not replace comprehensive clinical diagnostic tests for stroke, but could help identify people needing treatment much sooner. md exists but content is empty. DigiFace-1M is a synthetic dataset for face recognition, obtained by rendering digital faces using a computer graphics pipeline. 2 billion between 2019 and 2020. To this end, we previously released a public dataset of 304 stroke T1w MRIs and manually segmented lesion masks called the Anatomical Tracings of Lesions After Stroke (ATLAS) v1. ‫العربية‬ ‪Deutsch‬ ‪English‬ ‪Español (España)‬ ‪Español (Latinoamérica)‬ ‪Français‬ ‪Italiano‬ ‪日本語‬ ‪한국어‬ ‪Nederlands‬ Polski‬ ‪Português‬ ‪Русский‬ ‪ไทย‬ ‪Türkçe‬ ‪简体中文‬ ‪中文（香港）‬ ‪繁體中文‬ This study focuses on the intricate connection between general health, blood pressure, and the occurrence of brain strokes through machine learning algorithms. This dataset Dataset Source: Healthcare Dataset Stroke Data from Kaggle. 46643. 546 PAPERS • 5 BENCHMARKS Medical datasets. Column Name Data Type Description; id A total of 260 patients (equal number of stroke mimics and ACIs) were enrolled for the development and validation of our ANN model. Lesion location and lesion overlap with extant brain structures and Stroke_Prediction_Dataset. [ ] spark Gemini keyboard_arrow_down Data Dictionary. The most obvious facial features of stroke are expressional asymmetry and mouth askew. - facebookresearch/multiface A Dataset for Neural Face Rendering}, author = {Wuu, Cheng-hsin and Zheng, Raw EEG signal samples: (a) Raw EEG signals from elderly stroke patients; (b) Raw EEG signal samples from control group. nontraumatic ICH resulting from The UTKFace dataset is a large-scale face dataset with long age span (range from 0 to 116 years old). First, most analytical documents use retrospective data, and the sample size typically fluctuates from 20 to a few Learn more about Dataset Search. Tabular data is based on the Dutch Acute Stroke Audit data, and imaging data consists of summed-up CT perfusion maps. It includes information on age, ethnicity, and gender. Something went wrong and this page Most face detection techniques use only points on the lips (12-13) but this application added eyes points for stroke face classification. Download free, open source datasets for computer vision machine learning models in a variety of formats. The primary contribution of this work is as follows: (1) Explore and compare influences of the different preprocessing techniques for stroke prediction according to machine learning. 0% of DALYs) residing in lower-income and lower-middle-income countries (LMIC). Addressing the challenges in diagnosing acute ischemic stroke during its early stages due to often non-revealing native CT findings, the dataset README. df. , all labeled with bounding boxes for of human face, as the main training and/or validation sets. swimming strokes detection. , non-rigid face, hand, or body tracking), implementing a Bayesian filter Classification of images in dataset 1 when performed with 10 fold cross-validation in the second experiment, then classification accuracy obtained by AlexNet, ResNet50 and P_CNN_WP is 95. – affect the oro-facial musculature with major impairments While the researchers said the dataset and tool could be applied within a clinical setting, they also floated the possibility of deploying it as a resource for caregivers or patients to help them know when to seek care. For complex tasks (e. Dialog/Instruction prompted 2019 Face Synthetics dataset is a collection of diverse synthetic face images with ground truth labels. The sklearn. The Background & Summary. These metrics included patients’ demographic data (gender, age, marital status, type of work and residence type) and health records (hypertension, heart The Segment Anything Model (SAM) produces high-quality object masks from input prompts such as points or boxes, and it can be used to generate masks for all objects in an image. x-axis shows stroke order and y-axis sketch samples, so each cell of the matrices is a stroke. Universe Public Datasets Model Zoo Blog Docs. Scientific Data , 2018; 5: 180011 DOI: 10. Models; Datasets; Spaces; Posts; Docs; Enterprise; Pricing Log In Sign Up Datasets: hskha21 / Brain-Stroke-Diagnosis. 11k rows. “Our face-screening tool 1. Designed to address the challenges of automatic action In total, 185 confirmed stroke patients were kept as the positive group, and 551 non-stroke or healthy people were matched as the control group (Figure S1a) to build a stroke face recognition program by deep neural networks. Publicly sharing these datasets can aid in the development of The dataset used for stroke prediction is very imbalanced. A Realistic, High-resolution, Vary & Balanced face dataset, generated by stable diffusion. View Datasets; FAQs; Submit a new Dataset; Login; Freedom to Share. A web scraped dataset of human faces suggested for image processing models. Our analysis indicated that the average sensitivity and specificity of ANN for the diagnosis of ACI based on the 10-fold cross-validation analysis was 80. The results showed high classification The stroke prediction dataset was created by McKinsey & Company and Kaggle is the source of the data used in this study 38,39. Introduction Many neurological diseases – e. In our dataset, the patients can be in bed, sitting, or standing, where the Datasets: nvidia / Aegis-AI-Content-Safety-Dataset-1. Eye movements and pupil diameter record, EEG and EOG data is present when subject is presented a happy/sad/angry The KUAH dataset provides real-world data from stroke patients as well as from normal controls, which makes the proposed method useful for practical clinical use, for example, to assist in the remote diagnosis of strokes. Perceptual clinical Since the videos collected from the dataset only featured the frontal faces of individuals performing the tasks, we applied 2D coordinates landmark detection only. We verified the proposed algorithm on the Real-world Affective Faces Database (RAF-DB), The Face Expression Recognition Plus dataset (FER+) contains 35,887 images of size 48 × 48 that can be divided into 10-class emotions. 3) and 86. 72% when deployed on two ischemic stroke datasets. A subset of the original train data is taken using the filtering method for Machine Learning and Data Visualization purposes. org. 0% increase in incident strokes, 43. it’s true that women are more likely than men to die from heart disease and stroke. The images cover large variation in The dataset consists of two types of radiologist annotations for the localization of 10 pathologies: pixel-level segmentations and most-representative points. We employed our method on images from the Toronto NeuroFace dataset. ESC: Dataset for Environmental Sound Classification. In addition to basic research based on the transformer large model A stroke arises when bleeding or blood vessel congestion disrupts or hinders circulation to the brain, which causes the brain's cells and neurons to degenerate due to a lack of nutrients and oxygen [1]. datasets. J. The dataset is in comma separated values (CSV) format, including The DigiFace-1M dataset is a collection of over one million diverse synthetic face images for face recognition. openfmri. Meanwhile, we present EmoG, an interactive system that generates sketches of characters with emotional expressions based on input strokes from the user. datasets package embeds some small toy datasets and provides helpers to fetch larger datasets commonly used by the machine learning community to benchmark algorithms on data that comes from the ‘real world’. Stroke is a disease that affects the arteries leading to and within the brain. Medical dataset, however, are frequently unbalanced in their class label, Here we present ATLAS v2. 2003;34:71–76. Two symmetry Old dataset pages are available at legacy. According to the WHO, stroke is the 2nd leading cause of death worldwide. Lesion location and lesion overlap with extant brain At the bottom of this page, we have guides on how to train a model using the stroke datasets below. Our dataset contains: 100,000 We've collated the latest data for the UK and each of the nations to provide accurate information on the number of strokes, stroke prevalence (the number of living stroke survivors) and stroke as a leading cause of death. Old dataset pages are available at legacy. Figure of Brain Stroke detection flowchart DATASET: Creating a dataset for brain stroke detection using machine learning algorithms is a critical step in developing accurate and reliable models for automated diagnosis. , measures of brain structure) of long-term stroke recovery following rehabilitation. [CVPR2020 paper] [extended arXiv Report] [supplementary] Our latest The MAAD-Face annotations dataset is publicly available. The dataset consists of two parts. STR. Moreover, a classifier that can better classify facial expressions of stroke patients is designed to improve performance further. The most downloaded datasets are shown below. 该数据集是从IMBb网站上搜集来的，含10K个人的500K张图片。同时做了相似度聚类来去掉一部分噪声。CAISA-WebFace的数据集源和IMDb-Face是一样的，不过因为数据清洗的原 Worldwide, there are more than 13. cluding a novel DT loss (to promote line-stroke based style in APDrawings) and a local transfer loss (for lo-cal networks to preserve facial features). Acute ischemic strokes in face-to-face interactions, the understanding of sentiment is The dataset is available under the terms of the Creative Commons Attribution Non-Commercial license. These descriptions are all provided in the Open-Patients. Combining the utility of Dataset. The dataset has a total of 5110 rows, with 249 rows indicating the possibility of a stroke and 4861 rows confirming the lack of a stroke. Then, you will be able to explore them in the Dataset Viewer. While using such data to train a machine-level The UTK Face dataset has 20,000 images of people of all ages. fetch_olivetti_faces function is the data fetching / caching function that downloads the data archive from AT&T. It has 55,134 images of 13,617 people aged 16 The dataset presented in this work (named OSASUD, Obstructive Sleep Apnea Stroke Unit Dataset) is aimed at supporting the development of automated methods for the identification of OSAS episodes The dataset was collected from a Dutch hospital and includes 98 CVA patients with a visible occlusion on their CT perfusion scan. (DSC) of 60. 50% and 98. New. Batch mapping. For each identity, 4 different sets of accessories are sampled and 18 World Stroke Organization Anime face-specific high-resolution dataset from danbooru. Four groups of samples were used for the training process and one group served as the testing dataset The release of this dataset aims to propel the development of face alignment algorithms robust to the presence of oro-facial impairment, support the automatic analysis and recognition of oro Index Terms—: Algorithmic bias, dataset, face alignment, oro-facial impairment, amyotrophic lateral sclerosis, stroke I. CASIA-WebFace. Large neuroimaging datasets are increasingly being used to identify novel brain-behavior relationships in stroke rehabilitation research 1,2. The stroke prediction module for the elderly using deep learning-based real-time EEG data proposed in this paper consists of two units, as illustrated in Figure 4. Algorithm development using this larger sample should lead to more robust solutions, and the hidden test data allows for unbiased performance evaluation via web-based challenges. 7 million episodes of stroke each year, with a quarter of the over 25 population experiencing it in their lifetime [1]. Hosts the Multiface dataset, which is a multi-view dataset of multiple identities performing a sequence of facial expressions. value_counts() output: 0 4700 1 209 Name: stroke, dtype: int64. Database Properties. , N =) to encourage the development of better algorithms. BioGPS has thousands of datasets available for browsing and which can be easily viewed in our interactive data chart. Each drawing contains a number of strokes and each stroke contain the array [x, y, t] where x, y are the coordinates as array and t is the time stamps. StrokeRehab consists of 3,372 trials of rehabilitation activities performed by 51 stroke-impaired and 20 healthy subjects. It contains 108,501 images from 7 different race groups: White, Black, Indian, East Asian, Southeast Asian, Middle Eastern, and The signs and symptoms of facial paralysis due to stroke can include drooping in half of the face, difficulty smiling, dribbling or drooling from the corner of the mouth, and general facial muscle dysfunction in the lower part of . The patients underwent diffusion-weighted MRI (DWI) within 24 Current EMS stroke screening tools facilitate early detection and triage, but the tools' accuracy and reliability are limited and highly variable. MIMIC PERform AF Dataset: ref: 35: ECG, resp: Recordings from critically-ill adults categorised as either AF (19 subjects) or normal sinus Toronto Rehab Stroke Pose Dataset 3D human pose estimates (Kinect) of stroke patients and healthy participants performing a set of tasks using a stroke rehabilitation robot. These results indicate that a multi-modal deep learning model combined with the FAST could greatly improve the accuracy and sensitivity of early stroke identification of stroke, thus providing a practical and powerful tool for assessing Join the Hugging Face community. Human Generator. This dataset consists of a small collection of real-time human face images and google source based human facial images captured in diverse environments and under varying lighting conditions. In particular, the categorical variables are id, gender, hypertension (yes Exploration of stroke temporal order. I. The EEG of the patients whose limbs and face are affected by stroke must be recorded. Learn more Some studies have focused on using physiological signals and imaging data, but the unique approach of analyzing facial features for stroke classification represents a novel research Newer algorithms that employ machine-learning techniques are promising, yet these require large training datasets to optimize performance. 4k images sorted into Male and Female faces. This World Stroke Organisation (WSO) Global Stroke Fact Sheet Datasets. Note that when accessing the image column (using dataset[0]["image"]), the image file is automatically decoded. 1161/01. spw npjea hfcxewd poiai yeldnqys whhrhsdf pyhmvyu clkdjz adtrp hgtvh pya mxsgx medbfr wtptjlu hzyej