Okes2024 / Machine-Learning-to-Predict-Suicide-RiskLinks
This project applies machine learning to predict suicide risk using synthetic psychological, demographic, and behavioral data. It demonstrates risk classification with Logistic Regression and Random Forest, evaluates performance metrics, and visualizes insights, highlighting the potential of AI in mental health research and awareness.
☆17Updated last month
Alternatives and similar repositories for Machine-Learning-to-Predict-Suicide-Risk
Users that are interested in Machine-Learning-to-Predict-Suicide-Risk are comparing it to the libraries listed below
Sorting:
- ☆17Updated 5 months ago
- Goal: Develop ML models to identify high-risk patients for hospital readmission within 30 days of discharge. Approach: Analyze clinical d…☆17Updated last month
- A prototype chatbot that analyzes symptoms using ML, suggesting possible conditions based on synthetic data. Educational use only, demons…☆17Updated 2 weeks ago
- ☆12Updated 5 months ago
- This project forecasts renewable energy demand using LSTM-based time series models. It processes historical demand data, trains predictiv…☆18Updated 2 weeks ago
- ☆17Updated 5 months ago
- This project applies machine learning to detect bias in recruitment decisions, analyzing gender disparities using fairness metrics like D…☆17Updated last week
- This project uses NLP to analyze synthetic patient journals for anxiety trends. It applies text preprocessing, scoring, and topic modelin…☆17Updated last month
- Machine learning to optimize team formation by clustering individuals based on personality traits and strategically forming diverse teams☆17Updated 2 months ago
- ☆12Updated 5 months ago
- This project demonstrates building a synthetic mental health support chatbot. It generates a labeled dataset, trains an intent classifier…☆17Updated this week
- ☆12Updated 5 months ago
- The use of advanced remote sensing technologies to measure atmospheric concentrations of gases like carbon dioxide (CO₂), methane (CH₄), …☆11Updated 11 months ago
- Climate Change Impact Analysis is a Python-based application designed to explore and analyze datasets related to temperature, precipitati…☆11Updated 8 months ago
- ☆17Updated 5 months ago
- ☆17Updated 5 months ago
- This project develops a machine learning model to predict employee job satisfaction based on key organizational factors. The solution hel…☆17Updated 2 months ago
- project leverages synthetic VR session data to analyze patient responses in exposure therapy. Using statistical and visualization techniq…☆17Updated last month
- ☆12Updated 5 months ago
- This project generates synthetic ADHD and control patient data, applying machine learning and statistical analysis to uncover behavioral …☆17Updated 3 weeks ago
- Text Mining in Employee Feedback Surveys applies natural language processing to analyze employee comments, uncover hidden themes, sentime…☆17Updated 2 weeks ago
- Synthetic modeling of Urban Heat Islands (UHI) using satellite-like data. Generates spectral bands, vegetation and urban indices, and lan…☆17Updated last month
- Goal: Predict future employee performance using historical Key Performance Indicators (KPIs). Method: Apply ML models to analyze produc…☆17Updated last month
- This project leverages machine learning and deep learning to analyze synthetic voice features for detecting potential emotional disorders…☆17Updated last month
- Objective: Predict chronic disease onset using Electronic Health Records (EHRs). Method: Apply ML algorithms to identify high-risk pati…☆17Updated 2 weeks ago
- This project uses Natural Language Processing (NLP) to perform sentiment analysis on internal communications, helping organizations under…☆17Updated last week
- A Chart for Water Parameters is a visual representation of key water quality indicators, such as pH, turbidity, dissolved oxygen, conduct…☆11Updated 7 months ago
- This project predicts the quality of water based on various water parameters and pollutants using machine learning and deep learning tech…☆11Updated 7 months ago
- Okes2024 / Utilizing-Machine-Learning-and-DSAS-to-Analyze-Historical-Trends-Forecast-Future-Shoreline-ChangeThe dynamic nature of forecasting shoreline changes in the Niger Delta over 50 years (1974–2024) by leveraging satellite imagery and mac…☆12Updated 6 months ago
- ☆12Updated 5 months ago