Tech Xplore

Study finds 'dosed' nonlinearity can beat linear and fully nonlinear AI

Umbrella or sun cap? Buy or sell stocks? When it comes to questions like these, many people today rely on AI-supported recommendations. Chatbots such as ChatGPT, AI-driven weather forecasts, and ...

Benchmark of 1.4 million checked protein structures could sharpen AI predictions

University of Missouri researchers have released the world's largest collection of protein models with quality assessment—a groundbreaking new resource that could accelerate drug development for ...
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 data preprocessing. If you''ve ever built a predictive model, worked on a ...
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, ...
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 ...

AI can predict success of hip operations

Artificial intelligence can help to predict how well patients with hip osteoarthritis will be able to walk again after an ...
AHA/ASA Journals

Criteria to Assess the Predictive and Clinical Utility of Novel Models, Biomarkers, and Tools for Risk of Cardiovascular Disease: A Scientific Statement From the American Heart ...

Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...
IEEE

Design of a Generic Fault Diagnosis Model for Electrical Distribution Networks Using a Support Vector Machine (SVM) Algorithm

Abstract: This article presents the design and implementation of a generic model for fault diagnosis in electrical distribution networks, based on the Support Vector Machine (SVM) algorithm. The ...
Frontiers

Machine learning-based algorithms for the prediction of 90-day survival in patients with liver failure receiving artificial liver therapy

Background: Liver failure is associated with high short-term mortality, and the predictive value of clinical factors for patients undergoing artificial liver therapy is uncertain. We aim to develop ...
Frontiers

Postpartum depression risk prediction using explainable machine learning algorithms

1 Department of Science and Education, Shenyang Maternity and Child Health Hospital, Shenyang, China 2 Department of Maternal, Child and Adolescent Health, School of Public Health, Shenyang Medical ...