Latest AI and machine learning research in alternative medicine for healthcare professionals.
While general-purpose large language models (LLMs) demonstrate remarkable capabilities, their clinical application demands rigorous adaptation to ensure safety and accuracy. This review presents a comprehensive framework for transforming LLMs into trustworthy medical specialists. We detail three core knowledge-injection strategies-(1) static embedding to internalize foundational biomedical knowled...
Antimicrobial resistance (AMR) is a growing global health threat, yet the extent to which environmental resistomes reflect human disease burden remains unclear. In this study, we provide the first attempt to bridge freshwater resistomes with human disease burden using machine learning models, with a focus on identifying environmental signatures associated with drug-resistant tuberculosis (DR-TB) b...
The strengthening and growth of forensic science is vital for a Nation's law enforcement and criminal justice system. Forensic agencies serve the crim...
BACKGROUND: Artificial intelligence is increasingly applied to rehabilitation; however, persisting gaps in research, such as methodological heterogene...
Modern generative large language models (LLMs) are increasingly being evaluated in epilepsy-related clinical tasks, but the evidence remains fragmente...
BACKGROUND: Artificial intelligence (AI) is reshaping clinical decision support systems (CDSSs). In acute and critical care, nurses provide continuous...
BACKGROUND: Artificial intelligence (AI) is increasingly explored in veterinary neurology for pattern recognition, prediction and clinical decision su...
Rapid advances in artificial intelligence, sensor technologies, and image recognition have accelerated the transition toward digital and intelligent s...
OBJECTIVE: To develop an automated tool that performs classification and segmentation of endometrium for ectopic pregnancy diagnosis before gestationa...
BACKGROUND: Artificial Intelligence (AI) models for mammography classification is prone to shortcut learning because diagnostically relevant evidence ...
Thyroid cancer is one of the most prevalent malignancies of the endocrine system, comprising various subtypes such as papillary thyroid carcinoma (PTC...
Precision medicine requires computational methods that can integrate genomic, transcriptomic, proteomic, metabolomic, epigenomic, single-cell and spat...
Digital impressions are now central to contemporary dental workflows, driven by advances in CAD/CAM manufacturing and intraoral scanning technologies....
Cold stress limits alfalfa (Medicago sativa) growth and persistence, but public transcriptomic datasets differ widely in genotype, tissue, treatment d...
Alzheimer's disease (AD) and mild cognitive impairment (MCI) require accurate early diagnosis to support timely clinical intervention and disease mana...
INTRODUCTION: Osteoporosis and osteopenia, characterized by reduced bone mineral density (BMD), increase fracture risk, particularly in older adults. ...
BACKGROUND: Rehabilitation is a core component of health systems worldwide, yet its conceptual boundaries remain heterogeneous and difficult to operat...
Radiographic fracture-healing assessment is subjective and time-consuming, and existing automated methods often underuse the complementary information...
Tropical theileriosis, caused by the tick-transmitted apicomplexan parasite Theileria annulata, remains a major constraint on cattle production across...
Increasing evidence indicates that cellular senescence, metabolic dysfunction, stromal remodeling, and immune perturbation collectively contribute to ...