TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...
Tech Xplore on MSN

Pinpointing direction in noisy 2D data: New algorithm could improve imaging, AI, particle research and more

A University of Hawaiʻi at Mānoa student-led team has developed a new algorithm to help scientists determine direction in ...
Devdiscourse

AI-driven air quality system promises faster, more reliable urban health warnings

Read more about AI-driven air quality system promises faster, more reliable urban health warnings on Devdiscourse ...
Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
Scientific Research Publishing

Accuracy and Response Speed of Eye Center Annotation Using Eye Movement Models: Validating the Effectiveness of Eyesight Detection ()

Optokinetic Nystagmus (OKN) is a natural reflexive eye movement in oculomotor studies, reflecting the health status of the visual system. Through accurate eye center annotation, physicians can observe ...
University of California, San Francisco

AI Bots Accurately Analyze Big Data Set to Predict Preterm Birth

A team of UCSF researchers successfully tested several mainstream AI agents for the ability to analyze big data on women's ...
AHA/ASA Journals

Multistage Electrocardiographic Profiling for Mental Stress-Induced Myocardial Ischemia in Women: A Prospective, Age-Matched Cohort Study in China

BACKGROUND: Mental stress-induced myocardial ischemia is often clinically silent and associated with increased cardiovascular risk, particularly in women. Conventional ECG-based detection is limited, ...
The Lancet

When to and when not to use machine learning in risk prediction models

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

Machine learning model predicts serious transplant complications months before symptoms appear

A powerful artificial intelligence (AI) tool could give clinicians a head start in identifying life-threatening complications after stem cell and bone marrow transplants, according to new research ...
Frontiers

Data-Driven Approaches for Sustainable Geoscience: Machine Learning in Mineral Resources, Water Management, and Environmental Resilience

Machine learning has rapidly become integral to the advancement of geoscience, a field inundated with complex and multivariate data from myriad sources such ...

AI method accelerates liquid simulations by learning fundamental physical relationships

Researchers at the University of Bayreuth have developed a method using artificial intelligence that can significantly speed up the calculation of liquid properties. The AI approach predicts the ...