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

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

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

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.

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

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

A machine learning-based solution designed to predict metabolic syndrome risk using clinical, demographic, and lifestyle data.

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

Externally validated machine learning models for predicting caesarean section following induction of labour using real-world, population-based administrative datasets

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 repository contains the R code used to produce the manuscript: 'Development and internal validation of a risk-adjustment model for postoperative morbidity in adults undergoing major elective colorectal surgery: the Perioperative Quality Improvement Programme – colorectal risk model'