In a recent study published in Scientific Reports, researchers established a benchmark classification of major depressive disorder (MDD) using machine learning (ML) on cortical and subcortical ...

Adnan and colleagues evaluated machine learning models’ ability to screen for Parkinson’s disease using self-recorded smile videos. 2. The models achieved high sensitivity and specificity among ...

According to the authors, incorporating a broad spectrum of biomarkers allows the models to reflect the continuous and ...

A hybrid model combining LM, GA, and BP neural networks improves TCM's diagnostic accuracy for IPF, achieving 81.22% ...

Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease, and if it is accurately predicted ...

In a recent study published in Scientific Reports, researchers developed a machine learning-based heart disease prediction model (ML-HDPM) that uses various combinations of information and numerous ...

University of Idaho receives over $6M in DoD grants to advance machine learning research for PTSD diagnosis and military ...

Just like humans, artificial intelligence (AI) machine learning models are prone to bias. Understanding the nature of AI bias is paramount for critical applications that may impact life-or-death ...

New findings highlight the need to systematically check for bias in pathology AI to ensure equitable care for patients.

A recent study by Yale researchers demonstrated the potential of a machine learning approach to predict symptoms of post-traumatic stress disorder, or PTSD, for recent trauma survivors. Researchers ...