A poor night’s sleep may do more than leave one tired the next day — it could also signal serious health risks years in advance. Researchers from Stanford Medicine have developed a new artificial ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
In a study conducted at the University of Helsinki, AI was trained to classify bird sounds with increasing accuracy. The ...
Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease, and if it is accurately predicted ...
Background Prehospital delays remain critical barriers to timely acute coronary syndrome (ACS) care, particularly for ...
Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...
Abstract: Data privacy and heterogeneity among healthcare settings present fundamental challenges to machine learning (ML) brain tumor classification (BTC) model development based on local data. In ...
Abstract: Technology development has led to increased data generated in education, sparking interest in information extraction to support educational management through automated data analysis. Using ...
When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...
Background: To establish a classification model for assisting the diagnosis of type 2 diabetes mellitus (T2DM) complicated with coronary heart disease (CHD). Methods: Patients with T2DM who underwent ...
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