{"id":25992674,"url":"https://github.com/wizardoftrap/mental-health-predicter","last_synced_at":"2026-06-06T19:31:53.063Z","repository":{"id":280137647,"uuid":"941091416","full_name":"wizardoftrap/mental-health-predicter","owner":"wizardoftrap","description":"The Mental Health Prediction System utilizes a Flask API to deploy the machine learning model, while a Spring Boot API handles user interactions, stores data, and sends personalized mental health predictions via email.","archived":false,"fork":false,"pushed_at":"2025-03-01T13:26:34.000Z","size":167,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-01T14:27:34.654Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Java","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/wizardoftrap.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":"2025-03-01T13:18:18.000Z","updated_at":"2025-03-01T13:29:33.000Z","dependencies_parsed_at":"2025-03-01T14:27:45.655Z","dependency_job_id":"f18a1aca-01bc-481d-b02a-323bdbd1504a","html_url":"https://github.com/wizardoftrap/mental-health-predicter","commit_stats":null,"previous_names":["wizardoftrap/mental-health-predicter"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/wizardoftrap/mental-health-predicter","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/wizardoftrap%2Fmental-health-predicter","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/wizardoftrap%2Fmental-health-predicter/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/wizardoftrap%2Fmental-health-predicter/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/wizardoftrap%2Fmental-health-predicter/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/wizardoftrap","download_url":"https://codeload.github.com/wizardoftrap/mental-health-predicter/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/wizardoftrap%2Fmental-health-predicter/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":33997732,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-06T02:00:07.033Z","response_time":107,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"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":[],"created_at":"2025-03-05T14:28:44.946Z","updated_at":"2026-06-06T19:31:53.035Z","avatar_url":"https://github.com/wizardoftrap.png","language":"Java","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Mental Health Prediction System\n\nThis project predicts mental health conditions using a machine learning model trained with the Random Forest algorithm. The model is deployed using a Flask API, while a Spring Boot API handles user interactions, stores data, and sends predictions via email.\n\n## Tech Stack\n- **Machine Learning Model:** Random Forest\n- **Backend APIs:** Flask (ML Model), Spring Boot (User Interaction \u0026 Email)\n- **Database:** (Specify if used)\n- **Deployment:** Local or Cloud\n\n## How to Run the Project\n\n### 1. Prepare the Dataset\n- Create or load the dataset required for training.\n\n### 2. Train the Model\n- Train the model using the Random Forest algorithm.\n- Save the trained model for later use.\n\n### 3. Start the Flask API\n- Run the Flask application to deploy the ML model.\n- Ensure the API is accessible for predictions.\n\n### 4. Start the Spring Boot Application\n- Run the Spring Boot API to handle user requests.\n\n### 5. Make a Prediction Request\n- Send a request via the Spring Boot API, which forwards it to the Flask API.\n- The Flask API processes the data and returns the prediction.\n- The result is sent to the user via email.\n\n## Endpoints\n- **Flask API** – Handles ML model inference.\n- **Spring Boot API** – Manages user requests, stores data, and emails results.\n\n## License\nThis project is open-source. Feel free to modify and enhance it.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwizardoftrap%2Fmental-health-predicter","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fwizardoftrap%2Fmental-health-predicter","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwizardoftrap%2Fmental-health-predicter/lists"}