{"id":24746533,"url":"https://github.com/singhvishal003/brain_stroke_prediction","last_synced_at":"2026-04-13T20:01:57.426Z","repository":{"id":264294374,"uuid":"892635675","full_name":"Singhvishal003/Brain_Stroke_Prediction","owner":"Singhvishal003","description":"Brain Stroke Prediction according to age and Health Condition.","archived":false,"fork":false,"pushed_at":"2024-11-23T07:16:11.000Z","size":897,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-23T01:25:25.658Z","etag":null,"topics":["matplotlib","numpy","pandas","sklearn"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Singhvishal003.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-11-22T13:41:45.000Z","updated_at":"2024-11-25T05:44:47.000Z","dependencies_parsed_at":"2024-11-23T10:03:58.233Z","dependency_job_id":null,"html_url":"https://github.com/Singhvishal003/Brain_Stroke_Prediction","commit_stats":null,"previous_names":["singhvishal003/brain_stroke_prediction"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Singhvishal003/Brain_Stroke_Prediction","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Singhvishal003%2FBrain_Stroke_Prediction","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Singhvishal003%2FBrain_Stroke_Prediction/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Singhvishal003%2FBrain_Stroke_Prediction/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Singhvishal003%2FBrain_Stroke_Prediction/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Singhvishal003","download_url":"https://codeload.github.com/Singhvishal003/Brain_Stroke_Prediction/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Singhvishal003%2FBrain_Stroke_Prediction/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31768649,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-13T15:25:13.801Z","status":"ssl_error","status_checked_at":"2026-04-13T15:25:09.162Z","response_time":93,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["matplotlib","numpy","pandas","sklearn"],"created_at":"2025-01-28T04:29:05.181Z","updated_at":"2026-04-13T20:01:57.406Z","avatar_url":"https://github.com/Singhvishal003.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"## Brain Stroke Prediction Model Summary\n\n### Introduction\nStroke is a severe medical condition caused by the interruption of blood flow to the brain, leading to potential brain damage or death. Early prediction of stroke risk can significantly improve patient outcomes through timely intervention.\n\n### Key Factors\nThe model considers several critical factors:\n- *Age*: The risk of stroke increases with age.\n- *Health Conditions*: Conditions such as hypertension, diabetes, and cardiovascular diseases are significant risk factors.\n- *Symptoms*: Symptoms like sudden numbness, confusion, trouble speaking, and severe headache are crucial indicators.\n\n### Machine Learning Techniques\nThe model utilizes various machine learning algorithms to predict the risk of stroke:\n- *Decision Trees (DT)*\n- *Random Forest (RF)*\n- *Extra Trees (ET)*\n- *Voting Classifiers (VC)*\n\n### Data Handling\n- *Feature Selection*: Important features include age, gender, smoking status, and health conditions.\n- *Class Balancing*: Techniques like Synthetic Minority Oversampling Technique (SMOTE) are used to handle imbalanced datasets.\n\n### Performance Metrics\nThe model's performance is evaluated using several metrics:\n- *Accuracy*\n- *Precision*\n- *Recall*\n- *F1 Score*\n- *ROC-AUC Score*\n\n### Conclusion\nThe Voting Ensemble approach, which combines multiple models, provides the best performance with an ROC-AUC score greater than 0.95. Hypertension and cardiovascular diseases are identified as major risk factors for stroke.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsinghvishal003%2Fbrain_stroke_prediction","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsinghvishal003%2Fbrain_stroke_prediction","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsinghvishal003%2Fbrain_stroke_prediction/lists"}