Pharmacy professor develops AI model to predict hospitalization of at-risk cardiac patients

When Arinze Nkemdirim Okere, PharmD, MBA, worked as the pharmacist for a hospital in Tallahassee, Florida, he noticed that ...
The Daily Pennsylvanian

From data analysis to pattern recognition: Here’s how Penn Medicine is using artificial intelligence

Across the University of Pennsylvania Health System, scientists are now using AI to enhance their understanding of biological systems and modern medicine.

AI model detects prediabetes using ECG data without need for blood tests

DiaCardia, a novel artificial intelligence model that can accurately identify individuals with prediabetes using either ...
Drug Target Review

AI steps into drug safety: predicting liver injury earlier than ever before

Learn how AI is transforming predictions of drug-induced liver injury and aiding drug development for safer therapeutics.

How AI can detect health risks — just from the way you sleep

A new artificial intelligence model in the United States, SleepFM, has found that patterns in human slumber can be used to ...
Frontiers

Machine learning models for the prediction of levodopa response to tremor in Parkinson’s disease

Objectives: To develop and validate machine learning models to predict levodopa responsiveness of tremor in Parkinson’s disease (PD) patients. Methods: A total of 197 PD tremor patients underwent ...
EurekAlert!

ETRI releases no-code machine learning development tools

Since 2021, Korean researchers have been providing a simple software development framework to users with relatively limited AI expertise in industrial fields such as factories, medical, and ...
GitHub

multiple-disease-prediction

Multiple Disease Prediction System using Machine Learning. Predicts Parkinson's, Heart Disease, and Diabetes via a web interface powered by Logistic Regression, SVM, KNN, and Stacking Ensemble.
Frontiers

Machine learning-based prediction model for teicoplanin plasma concentrations in adults with liver disease using real-world data

Objective: To construct a prediction model for teicoplanin (TEIC) plasma concentrations through machine learning and deep learning techniques in patients with liver disease using real-world clinical ...
Rochester Institute of Technology

RIT researchers use machine learning to better understand the pathways of disease

Cancer, Alzheimer’s, and other diseases follow a pathway in the human body. It starts at the molecular and cellular levels, and through a series of complex interactions can lead to the development and ...
IEEE

Unified Disease Prediction System Using Machine Learning Techniques

Abstract: This innovative research uses datasets from Kaggle to leverage Machine Learning (ML) techniques to develop a complete unified disease prediction system. With its comprehensive coverage of ...