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

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.

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.

ML pipeline Portfolio project to predict cardiovascular risk using NHANES health survey data (2017-2018). XGBoost classifier with threshold tuning, ROC/PR evaluation, and automated reporting.

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

Global Shark Attack Warner is an interactive Flask-powered web app that uses a trained ML model to predict your shark-attack risk—High or Low—based on activity, shark species, time of day, attack type and location. With a dynamic beach background and playful shark animations, it makes exploring marine safety both informative and fun.

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'

Risk process simulation of insurance company PL PYTHON