Artificial Intelligence Medical Compendium

BACKGROUND: Physician compassion is associated with improvement in a variety of patient outcomes, but it remains unclear which individual physician behaviors affect patients' experience of compassion. OBJECTIVE: To determine which physician behaviors... read more 

BACKGROUND AND PURPOSE: Myocardial fibrosis (MF), a hallmark of structural cardiac remodelling, drives disease progression across most forms of heart failure and plays a central role in heart failure with preserved ejection fraction (HFpEF). Despite ... read more 

OBJECTIVES: To establish normative three-dimensional airway measurements in patients without dentofacial deformities (DDFs) or obstructive sleep apnea (OSA), and to identify anatomical and epidemiological factors associated with airway volume. METHOD... read more 

BACKGROUND: Patients with sepsis often exhibit a decrease in lymphatic numbers, which can be facilitated by protein arginine methyltransferase (PRMT). However, it is unclear how PRMT contributes to lymphopenia in sepsis. METHODS: This study employed ... read more 

Physics-Informed Neural Networks (PINNs) have shown great potential for solving partial differential equations (PDEs). However, their performance is often limited when dealing with multi-scale structures and high-frequency solution components due to ... read more 

Anomaly detection or one-class classification (OCC) plays a vital role in real-world applications. Traditional support vector machine-based OCC models often face challenges with large-scale datasets and are sensitive to the choice of kernel functions... read more 

The 5th edition of the WHO CNS tumor classification (2021) emphasizes molecular alterations, especially in pediatric tumors, integrating histology with molecular profiling for precise diagnosis. Advances like DNA methylation profiling and Next Genera... read more 

Writing a scientific autobiography is challenging due to the many factors influencing an academic career, including personal experiences, the era of one's career, research interests, available research tools, institutional environment, societal prior... read more 

Accurate prediction of drug-drug interactions (DDIs) is paramount for preventing adverse drug events and ensuring patient safety. While existing computational methods show promise, they often struggle to effectively model long-range intramolecular de... read more 

Drug synergy prediction plays a vital role in the discovery of effective cancer combination therapies by identifying drug pairs that work better together than individually. However, exhaustive experimental testing of all possible combinations remains... read more