A machine learning model for prediction of preeclampsia risk using routinely collected data was feasible among pregnancies in ...

Worcester Polytechnic Institute (WPI) researchers have used a form of artificial intelligence (AI) to analyze anatomical changes in the brain and predict Alzheimer's disease with nearly 93% accuracy.

How people with compromised immune systems respond to vaccines is an important area of immunological research. A study led by ...

As we begin a new year, many of us are thinking about our health and making resolutions to improve it. But what does the future hold?

When Hend Alqaderiwas studying how saliva could predict the risk of diabetes or the severity of a coronavirus infection, she collected a lot of saliva samples-thousands, measuring hundreds of bacteria ...

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...

Yale researchers have developed a machine learning model, called Immunostruct, that can help scientists create more ...

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...

A comprehensive healthcare AI application that leverages machine learning to predict diabetes risk based on medical parameters. Built with Flask and scikit-learn, featuring professional architecture ...

Production-ready machine learning system that predicts bike rental demand using real-world public APIs and historical data. Built with Docker-first architecture for seamless deployment, the system ...

Objective To systematically consolidate the most consistently applicable risk factors and assess their predictive performance for gestational diabetes mellitus (GDM) prediction. Design Systematic ...