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)

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.

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

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

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

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

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

Create risk assessment model on parsed text medical records

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.

Industrial Thesis in Machine Learning for the achievement of Master of Science in Computer Science.