Explore the implications of AI errors in health care and the necessity for human oversight in drug prescribing.

A team of industry leaders and the University of North Dakota are targeting the nation’s $966 billion chronic disease ...

Prevention, personalization, and empathy take center stage in these 15 bold predictions for the biggest research-driven breakthroughs of 2026.

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

Introduction Maternal and child mortality has markedly decreased worldwide over the past few decades. Despite this success, the decline remains unequal across countries and is overall insufficient to ...

Donald Trump’s destruction of the civil service is a tragedy not just for the roughly 300,000 workers who have been discarded ...

Twenty-five years of research into complex systems shows why artificial intelligence will always produce errors in healthcare ...

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 ...

ABSTRACT: Smart health refers to the integration of cutting-edge technologies into healthcare systems to improve patient care and apply intelligent clinical decision-making. The study investigates how ...

1 Department of Computer Science, National University of Modern Languages (NUML), Islamabad, Pakistan 2 Department of AI and SW, Gachon University, Seongnam, Republic of Korea Cardiovascular diseases ...

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 ...