Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 20,271 to 20,280 of 215,962 articles

Spatiotemporal skeleton based learning for automatic exercise quality assessment and real time posture correction.

Scientific reports
BACKGROUND: Home-based fitness training requires automated systems for exercise quality assessment and real-time posture correction without professional supervision. PURPOSE: We develop an AI-powered virtual fitness system using spatiotemporal skelet... read more 

Serum KIM-1 molecular early warning radar: SERS combined with artificial intelligence for accurate early diagnosis of chronic kidney disease.

Mikrochimica acta
Chronic kidney disease (CKD) has become a major global public health issue. Due to its insidious onset and atypical early symptoms, patients often fail to detect it in time and receive effective intervention. Therefore, conducting early screening and... read more 

An engineering-informed voting ensemble framework for rapid seismic risk screening of reinforced concrete structures.

Scientific reports
Rapid evaluation of existing building stocks is essential for reducing earthquake-related disaster risk, particularly in seismically vulnerable cities such as Gaziantep, Türkiye. However, commonly used assessment approaches are either time-consuming ... read more 

A triaxial benchmark for assessing responses from large language models in traditional Chinese medicine.

Communications medicine
BACKGROUND: Large language models (LLMs) show promise in specialized domains, but their capabilities in Traditional Chinese Medicine(TCM)-a field with complex theoretical foundations and clinical practices-remain inadequately assessed. This study aim... read more 

Machine learning empowers precise discovery of disease-resistance genes in plants.

Plant physiology
Identifying plant disease-resistance genes is essential for understanding the plant immune system and accelerating the breeding of disease-resistant crops. There is a pressing need for a method capable of accurately identifying plant disease-resistan... read more 

Bridging Therapeutics and Nanotechnology in Dry Eye Disease: A Review of Risk Factors, Drug Delivery Barriers, and Recent and Future Endeavors for Disease Management.

AAPS PharmSciTech
Dry eye disease (DED) is a multifactorial ocular disorder with high prevalence among global population, characterized by tear film instability, hyperosmolarity, and ocular surface inflammation, leading to impaired vision and reduced quality of life. ... read more 

Lumbar, thoracic, and bilateral vertebral body tethering: do surgical outcomes differ?

Spine deformity
PURPOSE: VBT is increasingly being used in the lumbar spine to preserve mobility. Surgeons have noted differences in complications and outcomes among single thoracic (T), single lumbar (TL/L), and bilateral (B) VBT, but evidence has been limited to s... read more 

Enhancing Anatomy Learning Through Enhanced 3D Visualization: A Study on Student Perception and Engagement in Museum-Based Education.

Journal of imaging informatics in medicine
Effective anatomy education is essential for medical training. While traditional anatomy instruction provides essential foundational knowledge, its effectiveness depends on the instructional format, level of interaction, and availability of clinical ... read more 

Structural imaging predictors of ketamine response in treatment-resistant depression: a machine learning approach.

Translational psychiatry
Ketamine has demonstrated rapid antidepressant efficacy in treatment-resistant depression (TRD), but clinical decision-making is challenging due to variability in individual response. Current trial-and-error prescribing practices may expose patients ... read more 

Assessing urbanisation and ecological integrity coupling in Malaysia using interpretable machine learning.

Scientific reports
Urbanisation-environment interactions are increasingly non-linear, yet traditional Coupling Coordination Degree (CCD) frameworks often rely on static, linear assumptions that fail to capture complex feedback loops. This study proposes an integrated f... read more