Medical Xpress

Machine learning can predict patients' responses to antidepressants—while disentangling drug and placebo effects

Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global population. It is characterized by a persistent low mood, disruptions in typical ...
The Indianapolis Star

Should you be using a smaller snow shovel? Heart experts recommend it, actually

Note: A previous version of this story was published on Jan. 9, 2025. If you're headed out to shovel a path after Indiana's most recent snowfall, the American Heart Association has encouraged Hoosiers ...
Scientific Research Publishing

Heart Disease Prediction: A Logistic Regression Approach ()

1 School of Computing and Data Science, Wentworth Institute of Technology, Boston, USA. 2 Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA. 3 ...
Scientific Research Publishing

Analysis of Decision Support Systems (DSS) Integration with AI Using Mobile Health (m-Health) and Wearables ()

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 ...
New York Post

Long-term use of this popular sleep supplement linked to 90% higher risk of heart failure

Having trouble falling asleep? Hang on before reaching for the melatonin. A new study says chronic use of the sleep aid may lead to heart failure — but experts say you shouldn’t panic just yet. While ...
National Academies of Sciences%2c Engineering%2c and Medicine

Making Machine Learning Safer in High-Stakes Settings

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...
IEEE

IoT-Enabled Heart Disease Risk Prediction Using Machine Learning Algorithms: A Comparative Analysis of ML Models

Abstract: This Study will explore how the IoT and machine learning predict heart disease risks through real-time wearable device and sensor data. The Cleveland and Hungarian datasets have relevant ...
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 ...
Frontiers

Heart disease prediction with a feature-sensitized interpretable framework for the Internet of Medical Things sensors

Introduction: Cardiovascular health is increasingly at risk due to modern lifestyle factors such as obesity, smoking, stress, hypertension, and sedentary behavior. Post-pandemic health practices and ...
news.ucsc

‘Future-guided’ AI improves seizure prediction

In the world around us, many things exist in the context of time: a bird’s path through the sky is understood as different positions over a period of time, and conversations as a series of words ...
news.ucsc

WiFi signals can measure heart rate—no wearables needed

Computer Science and Engineering Ph.D. student Nayan Bhatia demonstrates Pulse-Fi, technology that uses WiFi signals to measure a person's heart rate. Heart rate is one of the most basic and important ...