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.

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

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

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)

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.

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

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

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

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.

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.

The aim of this project is to predict the risk of osteoporosis in patients using a dataset of patients' medical records. Osteoporosis is a condition that weakens bones, making them fragile and more likely to break. It develops slowly over several years and is often only diagnosed when a minor fall or sudden impact causes a bone fracture.

End-to-end EHR risk prediction pipeline using MLOps stack — MLflow, FastAPI, Docker, and config-driven training.