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.
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.
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 ...
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 ...
AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...
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.
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 ...
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