Wildfire risk assessment using remote sensing data - Prediction of Wildfires

A comparative analysis of 4 ML algorithms. This Hypertension Risk Prediction Model can be described as a machine learning model designed to predict an individual's risk of developing hypertension based on various input parameters.

Deep learning to estimate lung-related mortality from chest radiographs.

A machine learning algorithm to create risk score models for risk prediction

MIEO (Masked Input Encoded Output): self-supervised embeddings for clinical tabular data; handles missing values and mixed types for CVD risk prediction.

Prognostic ML-models and key-feature extraction for analysis of cardiovascular complications

MICCAI 2024: Ordinal Learning: Longitudinal Attention Alignment Model for Predicting Time to Future Breast Cancer Events from Mammograms

Acute Lung Injury Code for Paper Submitted to AMIA. Experimented with a wide range of ML algorithms to predict the risk of Acute Lung Injury for intensive care unit patients in 24-hour intervals using demographic and clinical observation features.

multiPGS_py is a fast, simple and low-memory python method to calculate polygenic scores (PGS/PRS)

Digital lifestyle benchmark dataset (3,500 synthetic records, 24 features) for mental wellbeing risk modeling (high_risk_flag) + reproducible notebooks.

A machine learning–powered early warning system for universities that identifies students at academic or scholarship risk through predictive modeling, visualization, and explainable decision support.

It is a Capstone project. A model has been created to predict for the heart diseases. It can be very useful for the health sector as cardiovascular diseases are rapidly increasing. The record contains patients' information. It includes over 4,000 records and 15 attributes.

Text Classification on reddit data for eRisk CLEF 2020 on the task of Risk Prediction.

Risk and Predictive Analytics in the Area of Car Insurance Planning and Marketing

Machine learning system that predicts heart disease risk using patient health data and visual insights

Graph based AI for early detection of underperformance in educational and organizational contexts implemented with Jac

Educational diabetes risk awareness web app — XGBoost model trained on BRFSS big data (2020–2024) using Google BigQuery & Cloud Storage + personalized prevention advice powered by Gemini 2.5-flash. Built with Streamlit. For Canada / North America.

SKLEARN-Credit Risk Prediction Using Logistic Regression Model, ML, Confusion Matrix, classification Report

AI-Driven Supply Chain Risk Analysis & Black-Box Optimization Platform

Create risk assessment model on parsed text medical records