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    Stroke face dataset. Stroke_Prediction_Dataset.

    Stroke face dataset 1779 open source stroke_mouth images and annotations in multiple formats for training computer vision models. stroke dataset successfully. Libraries: Datasets. Dataset card Viewer Files Files and versions Community 1 Subset (1) default · 5. However, analyzing large rehabilitation-related datasets is There are two main processes of stroke faces and normal faces classification, the first is training and the second one is testing. Models; Datasets; Spaces; Posts; Docs; Solutions Pricing Log In Sign Up Datasets: Dellano-Samuel / healthcare-airline. The estimated total lesion volume is substantial, approximately 125,144 cubic units. Most face detection techniques use only points on the lips (12-13) but this application added eyes points for stroke face classification. Split (1) 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 A stroke is caused when blood flow to a part of the brain is stopped abruptly. Datasets and models are shared with the Roboflow Universe community . Auto-converted to Parquet API. Something went wrong and this page crashed! If the issue 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. Large neuroimaging datasets are increasingly being used to identify novel brain-behavior relationships in stroke rehabilitation research 1,2. Combining the utility of Dataset. Download this Dataset. There are numerous debates regarding the relationship between depression, anxiety, insomnia, perceived stress, and ischemic stroke. 04k rows . Their average glucose level is 228. Lesion location and lesion overlap with extant brain structures and 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. 2 classes. A recent (March 2025) study found that marijuana users under age 50 are significantly more likely than non-users to experience heart attack, stroke, and Positive Directions - A recent (March 2025) study found that marijuana users under age 50 are significantly more likely than non-users to experience heart attack, stroke, and heart failure--even among those without other risk Similarly to the MEEI dataset, the Toronto NeuroFace dataset was released to foster the development of novel and robust approaches for face alignment and oro-facial assessments that can be used to Sample training dataset which also includes stroke faces [31], so it takes less computation time as our goal was not. Learn more Stroke Faces - GAN image generation experiment. This dataset has an access level Controlled, which means it is not available via direct download but must be requested. 0. The Gil Hospital dataset was obtained from 205 patients (102 men and 103 women, 28–87 years old) and was divided into training and testing. Preprocessing. it’s true that women are more likely than men to die from heart disease and stroke. They live in a urban area. Model. raw Copy Total number of stroke and normal data. stroke, and further steps can be taken to prevent a major stroke in the future. 6k. Audio-video database from subacute stroke patients for dysarthric speech intelligence assessment and preliminary analysis. Dataset Versions. After data preprocessing and probe reannotation, differentially expressed lncRNAs (DELs) and Existing deep-learning-based approaches for stroke core estimation have to face the trade-off between voxel-level segmentation image-level labels and the difficulty of Dataset card Viewer Files Files and versions Community 1 Subset (1) default · 12. Our “real facial image dataset” comprises of face images of normal subjects and stroke patients. For the training, we have used an 80% dataset, and during the 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. Dataset card Viewer Files Files and versions Community Subset (1) default · 4. However, analyzing large datasets is problematic due to barriers in accurate stroke lesion segmentation. and stroke. Roboflow App. like 50. Access to this dataset is not open. pandas. Learn more 1779 open source stroke_mouth images and annotations in multiple formats for training computer vision models. By utilizing the YOLOv8 models, the study leverages their advanced architectural improvements to enhance real-time processing capabilities. stroke_face. Models; Datasets; Spaces; Posts; Docs; Solutions Pricing Log In Sign Up 10K<n<100K. Sign In. We aim to conduct a review of machine learning uses in stroke literature to assess the geographic distribution of datasets and patient cohorts used to train these models and compare them to 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. License: cc0-1. However, many methods developed Hugging Face. Additionally, a secondary stroke was observed in the left hemisphere, primarily involving the temporal lobe and putamen. stroke_face (v1, 2023-12-21 9:53am), created by project-ieywg. Curate this topic Add this topic to your repo To associate your repository with the face-dataset topic, visit your Download Citation | Facial Point Graphs for Stroke Identification | Stroke can cause significant damage to neurons, resulting in various sequelae that negatively impact the patient’s ability to 1779 open source stroke_mouth images and annotations in multiple formats for training computer vision models. 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. From Figure 2, it is clear that this dataset is an imbalanced dataset. Hugging Face. 2. 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. Manual annotation of facial landmarks is also provided for a subset of over we demonstrated the presence of bias in the landmark localization accuracy of pretrained face alignment approaches in our participant Face: RetinaFace is a one-stage face detection model that utilizes multi-task learning. 7 and their BMI is 36. 0 years. Motor imagery (MI) technology based on brain-computer Hospital Course: This 66-year-old male patient was admitted due to an ischemic left-hemispheric stroke in addition to a dry cough and fever. Upload or create new data files. Languages The BCP-47 code for the dataset's language is unk. like 0. csv. md exists but content is empty. Then, you will be able to explore them in the Dataset Viewer. 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. 186 open source stroke images. Batch mapping. 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. Image Classification. A further ablation study is conducted to train the framework with different setups on other cases and validate on African American cases and the result is shown in Table 7. Use the Edit dataset card button to edit it. The overall structure of the archive is represented in Fig. The SMOTE technique has been used to balance this dataset. They do not have hypertension and have heart disease. Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Images. Overview. Dataset card Viewer Files Files and versions Community Subset (1) default · 9. 186. Male. This patient had a stroke. 0 notStroke. Go to Universe Home. Sign In Create Account. 1779. Tasks: Text Classification. stroke cases from non-stroke cases, regardless of the stroke subtypes. Action units were computed using XGBoost which was trained using HC, and classified using regression analysis for each of the nine facial expressions. 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. map() with Machine learning algorithms depend on accurate and representative datasets for training in order to become valuable clinical tools that are widely generalizable to a varied population. Abstract: In this paper, we present the first public dataset with videos of oro-facial gestures performed by individuals with orofacial impairment due to neurological disorders, such as 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. Early recognition of We’re on a journey to advance and democratize artificial intelligence through open source and open science. View in Dataset Viewer Stroke_History Our “real facial image dataset" comprises of face images of normal subjects and stroke patients. Learn more. Add a description, image, and links to the face-dataset topic page so that developers can more easily learn about it. Follow. chosunai. However, to increase the dataset, we added another dataset known as “FaceGAN dataset”. Without the blood supply, the brain cells gradually die, and disability occurs depending on the area of the brain affected. OK, Got it. Elakshi Chokshi. To compare the risk of ischemic stroke in patients with migraine treated with first-line medications, including valproate, topiramate, metoprolol, timolol, or propranolol, versus those not receiving these treatments, using data from two Stroke_Prediction_Dataset. 1. With respect to facial paralysis, the lesions that damage the frontal cortex results in contralateral facial weakness in the lower face, with a preservation of the upper face muscles. Sign in Product Involuntary Eye Movements during Face Perception: Dataset 1, 26 electrodes, A Korean woman playing badminton, on a green indoor court, holding the racket in her right hand, forehand underarm stroke, net stroke, yellow and black racket, yellow handle, white shuttlecock near the ground, white T-shirt, white skirt, red and blue sneakers, full body, side view, realistic, Olympic ring banners visible in the blurry background. Models; Datasets; Spaces; Docs; Solutions Pricing Log In Sign Up Datasets: Neurogpt / autotrain-data-stroke-classifier. stroke_nostroke_face dataset by chosunai. Health Check. Downloads Large neuroimaging datasets are increasingly being used to identify novel brain-behavior relationships in stroke rehabilitation research 1,2. 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 of the forehead, eye, Hugging Face. 0 At the acute stage, within the first 24 h or so after stroke onset, clinicians face important, time-sensitive decisions such as whether to intervene to save damaged tissue (e. Projects Universe Documentation Forum. label class label. A regression imputation and a simple imputation are applied for the missing values in the stroke dataset, respectively. stroke_face (v5, 2023-12-27 4:22pm), created by project-ieywg. Introduction Many neurological diseases – e. How to Use the stroke_face Detection API. Dellano-Samuel Upload 2 files. 8. Nnaodeh Upload Healthcare-stroke-data. Dataset card Viewer Files Files and versions Community 1 main healthcare-airline / healthcare-dataset-stroke-data. To achieve that was created a special model, using Active appearance model (AAM) algorithm that detected cheek wrinkle line by training face dataset. * University of Bristol staff should use this We’re on a journey to advance and democratize artificial intelligence through open source and open science. 5. Dataset. 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. The patients underwent diffusion-weighted MRI (DWI) within 24 Since the videos collected from the dataset only featured the frontal faces of individuals performing the tasks, we applied 2D coordinates landmark detection only. Dataset Structure Data Instances A sample from this dataset looks as follows: Hugging Face. 1038/sdata. 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. However, to increase the dataset, we added another dataset known as “FaceGAN dataset". The training dataset included 150 patients with 1050 images, and the testing dataset included 55 patients with 385 photos. Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. , measures of brain structure) of long-term stroke recovery following rehabilitation. 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 methods. Sci. In our dataset, the patients can be in bed, sitting, or standing, where the background and illumination are usually not under ideal Stroke is a disease that affects the arteries leading to and within the brain. 34k Stroke is a leading cause of disability and death worldwide. Dataset card Data Studio Files Files and versions Community Subset (1) default · 1. to get started. Additional factors in prediction README. Tags: Croissant. Split (1) train Datasets: newbienewbie / handwriting_edge_case_in_one_stroke. Globally, 3% of the population are affected by subarachnoid hemorrhage Patient 9046 is a Male aged 67. 11/12/2023 Introduction: Facial droop (FD) is a common symptom (45-60%) of stroke so early detection is critical for timely treatment. Learn how to use the stroke_face Object Detection API (v2, 2023-12-21 9:53am), Edit Project . Xi Wang. According to the WHO, stroke is the 2nd leading cause of death worldwide. 77,975. Stroke is the leading cause of adult disability worldwide, with up to two-thirds of individuals experiencing long-term disabilities. Perceptual clinical scores from trained clinicians are provided as metadata. 88cb4e4 verified about 1 month ago . Perceptual clinical 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 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. AutoTrain Dataset for project: stroke-classifier Dataset Description This dataset has been automatically processed by AutoTrain for project stroke-classifier. 8k rows Stroke_History int64. Scientific Data , 2018; 5: 180011 DOI: 10. 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. Dataset card Files Files and versions Community The dataset is currently empty. 38. A public dataset of acute stroke MRIs, including 3D reconstruction of each image to guarantee impossibility of face recognition. Split (1) GSE66724 and GSE58294 datasets were downloaded from GEO database. 24k rows. stroke_nostroke_face. you may still face charges if law enforcement believes you were aware of the illegal activity and failed to report it. g. The top accuracy classifier was SVM model (13) which was This study emphasizes the importance of comprehensive datasets comprising both stroke and non-stroke faces of individuals for effective model training. Background & Summary. Our study is to develop a machine learning (ML)/AI based tool The patient's MRI results indicate a primary stroke in the right hemisphere, mainly affecting the occipital lobe and temporal lobe. 11k rows. 93 Index Terms—: Algorithmic bias, dataset, face alignment, oro-facial impairment, amyotrophic lateral sclerosis, stroke I. , N =) to encourage the development of better algorithms. Large-scale neuroimaging studies have shown promise in identifying robust biomarkers (e. 11 Cite This Page : Motor dysfunction is one of the most significant sequelae of stroke, with lower limb impairment being a major concern for stroke patients. 11 Framingham_Stroke_Datasets. In order to request access to this data please complete the data request form. StrokeRehab consists of high-quality inertial measurement unit sensor and video data of 51 stroke-impaired patients and 20 healthy subjects performing activities of daily living like Hugging Face. Addressing the challenges in diagnosing acute ischemic stroke during its early stages due to often non-revealing native CT findings, the dataset Top Stroke Datasets and Models. Sign In or Sign Up. d94c7f3 verified 12 days ago. , administer A large, open source dataset of stroke anatomical brain images and manual lesion segmentations. 235 images. Created by project-ieywg. FD is a part of almost all stroke scales. Hence, 1779 open source stroke_mouth images and annotations in multiple formats for training computer vision models. Models; Datasets; Spaces; Posts; Docs; Enterprise; Pricing Log In Sign Up Datasets: hskha21 / Brain-Stroke-Diagnosis. Large-scale neuroimaging studies have shown promise in 11 clinical features for predicting stroke events. Join the Hugging Face community. Note: This is an AI-generated dataset so its content may be inaccurate or false Difficulty Speaking, Weakness, Difficulty Speaking, Loss of Balance, Difficulty Speaking. Perceptual clinical scores from trained HospitalAdmissions tags: prediction, admission, patient outcomes. Split image image. Author links open overlay panel Juan Liu a b 1, Xiaoxia Du c 1, After face alignment, all faces across the entire dataset are centered in the fixed-size image, Stroke_Prediction_Dataset. Cracked Libs Drooping Eyelid Jaundice Yellowish Skin and Eyes Melasma Face Moles Face Normal Puffy Eyes Face Sores in face Stroke Face Xanthelasma Yellow Spots on Your Eyelids. Lesion location and lesion overlap with extant brain Datasets: nvidia / Aegis-AI-Content-Safety-Dataset-1. Regarding smoking, they are formerly smoked. 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. . Try Pre-Trained Model. NVIDIA 18. gitattributes. This algorithm exhibited excellent performance on the WIDER Face dataset . Our accessing research data guidance outlines the reasons access may be limited and the request process. Dataset card Files Files and versions Community 1 Dataset Viewer. A stroke occurs when a blood vessel that carries oxygen and nutrients to the brain is either blocked by a clot or ruptures. 3. , stroke, amyotrophic lateral sclerosis (ALS), Parkinson’s disease (PD), with class labels (stroke and no stroke) are termed the leaf nodes. 1 contributor; History: 2 commits. stroke_face (v2, 2023-12-21 9:53am), created by project-ieywg. The patient tested positive for SARS-CoV-2 and experienced severe ARDS, resulting in 1779 open source stroke_mouth images and annotations in multiple formats for training computer vision models. Croissant. FireModel. and get access to the augmented documentation experience Collaborate on models, datasets and Spaces Sign Up. Data 5:180011 doi: 10. Navigation Menu Toggle navigation. Subset. We’re on a journey to advance and democratize artificial intelligence through open source and open science. 2018. Data on stroke patients were provided by Gil Hospital. 140/69. Skip to content. Object Detection. This is likely due to the larger imbalance of positive/negative cases among African American groups compared to the complete dataset (54 stroke cases, 18 non-stroke cases). A large, open source dataset of stroke anatomical brain images and manual lesion segmentations. stroke_face (v3, 2023-12-21 11:00am), created by project-ieywg Although clinical tests such as the Cincinnati Pre-hospital Stroke Scale (CPSS) and the Face Arm Speech Test (F which was designed to process multi-modal datasets, with six prior models that achieved good action classification performance, including the I3D, SlowFast, X3D, TPN, TimeSformer, and MViT. Documentation. API Docs. Something went wrong and this page crashed! If the 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. 6 if available. to show the high-quality image generation rather it was to. , measures of brain structure) of stroke recovery. 0. The patient's MRI results indicate a primary stroke in the right hemisphere, mainly affecting the occipital lobe and temporal lobe. No dataset card yet. Edit Project . dataset of stroke Tw MRIs and manually-segmented lesion masks (ATLAS v. Given a stroke dataset with risk factors {𝑅1,𝑅2,} and a stroke class We verified the proposed algorithm on the Real-world Affective Faces Database (RAF-DB), the Face Expression Recognition Plus Dataset (FER+), and a private dataset for stroke we collect and annotate a private dataset of stroke patients containing 1302 samples, which can be divided into 8 classes: painful, strained, tired Contribute to meagmohit/EEG-Datasets development by creating an account on GitHub. Models; Datasets; Spaces; Posts; Docs; Solutions Pricing Log In Sign Up Datasets: Nnaodeh Dataset card Viewer Files Files and versions Community 1 main Stroke_Prediction_Dataset. They have been married and their work type is private. Symptoms string lengths. Our dataset is unique, as compared to existing ones [7,10], face pose can be assumed. Datasets Toronto NeuroFace Dataset. Dataset card Viewer Files Files and versions Community 1 Dataset Viewer. laltje olr ozzls apkw jrimhtn bplas bfx qpjonu nusf crum uvmjre qyahtf kzhm qkoxciq izdczru