Latest AI and machine learning research in primary care for healthcare professionals.
This study investigates health sciences students' attitudes toward artificial intelligence (AI) and the implications for ethical awareness, clinical decision-making, and public health. A cross-sectional survey was conducted between April 27 and May 15 2025, with 668 students from five departments at Gümüşhane University, employing the validated Artificial Intelligence Attitude Scale, which measure...
Artificial intelligence (AI) is increasingly transforming health care, particularly in solid organ transplantation, where it addresses complex challenges such as organ allocation, graft rejection prediction, and immunosuppressive management. This bibliometric analysis evaluated the scientific impact and evolution of AI applications in kidney, liver, heart, and lung transplantation. A comprehensive...
BACKGROUND AND OBJECTIVES: Low-grade systemic inflammation contributes to the pathophysiology of severe mental illness (SMI) in a substantial subset o...
Clinical trial enrollment in oncology remains limited by increasingly complex eligibility criteria, biomarker stratification, and fragmented clinical ...
Wearable biosensors leverage microfluidic technology for precise biofluid sampling and directional transport, and utilize electrical or optical sensin...
UNLABELLED: Depression and obesity are highly comorbid and likely involve common risk factors and pathophysiological mechanisms, which could crosslink...
BACKGROUND: Gestational diabetes mellitus (GDM) is a common complication during pregnancy, with its incidence increasing year by year. It poses numero...
BACKGROUND: Diabetic retinopathy (DR) remains a leading cause of preventable blindness, yet screening programs across Europe face persistent workforce...
AIM: To build a comprehensive nursing risk model for older adults inpatients with multiple chronic conditions to identify nursing risks. METHOD: This ...
The healthcare community remains divided on the benefits of artificial intelligence (AI) in medicine. In this qualitative study, we sought to better u...
Virtual screening has emerged as one of the most impactful in silico approaches for the identification of novel drug candidates, substantially reducin...
Lateral flow assay (LFA) is the most widely used point-of-care (PoC) diagnostic tools due to their simplicity, rapid turnaround, portability, and low ...
Dentists are often the first healthcare providers to observe subtle orofacial and behavioral changes that may reflect underlying neurological diseases...
Respiratory syncytial virus (RSV) is a leading cause of severe respiratory illness, imposing a significant burden on global health and society. Here, ...
BACKGROUND AND OBJECTIVE: The diagnosis of carotid plaques plays an important role in revealing cardiovascular and cerebrovascular diseases, thus attr...
BACKGROUND: The interplay between frailty dynamics and the newly defined Cardiovascular-Kidney-Metabolic (CKM) syndrome remains poorly understood. We ...
OBJECTIVES: To develop and validate CT-based radiomics models for the identification of chronic pancreatitis (CP) and selected CP-related complication...
BACKGROUND: Total joint arthroplasty (TJA) complications necessitate the development of accurate risk prediction models; however, interpretability in ...
BACKGROUND: Abdominal aortic calcification (AAC) is a subclinical measure of atherosclerotic cardiovascular disease (ASCVD). AAC can be captured on la...
Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease, while non-alcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver di...