Wildfire risk assessment using remote sensing data - Prediction of Wildfires

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

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.

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

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.

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

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

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

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

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.

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

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

Create risk assessment model on parsed text medical records

🤖 AI-powered Scrum automation toolkit with Slack/Trello integration, risk prediction, and task prioritization. Features ML models and Streamlit dashboard.

A tool for predicting the chance of breast cancer based on data.

A web app to demonstrate the usage of Wasm-iCARE to calculate the absolute risk of breast cancer.

The Loan Default Risk Analysis project predicts the likelihood of loan defaults using historical data, applying machine learning algorithms to assess financial risks. It helps in making informed lending decisions by analyzing borrower behavior and financial profiles.

This project is created to predict risk credit card loan of a bank using Classification Machine Learning Model

Predicting kidney stone risk using CNNs on genetic data, analyzing 400+ SNPs for precise risk stratification with Polygenic Risk Scores (PRS)

Code for the paper "Cardiac Complication Risk Profiling for Cancer Survivors via Multi-View Multi-Task Learning", published on ICDM 2021.