Artificial Intelligence Medical Compendium

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

Showing 71,391 to 71,400 of 234,892 articles

Deep learning models for radiography body-part classification and chest radiograph projection/orientation classification: a multi-institutional study.

European radiology
OBJECTIVES: Large-scale radiographic datasets often include errors in labels such as body parts or projection, which can undermine automated image analysis. Therefore, we aimed to develop and externally validate two deep-learning models-one for categ... read more 

AI-driven diagnosis of vulnerable intracranial atherosclerotic plaques using large language models and vision transformers: a multi-center study.

European radiology
OBJECTIVES: High-resolution vessel wall imaging (HR-VWI) is essential for diagnosing vulnerable intracranial atherosclerotic plaques, but its interpretation requires expertise. This study investigates the integration of large language models (LLMs) a... read more 

AAPPE: Protein-Ligand Binding Affinity Prediction Leveraging Amino Acid Pair Positional Encoding in Deep Learning.

Journal of chemical information and modeling
Accurate prediction of protein-ligand binding affinity is vital for accelerating drug discovery, yet challenges persist in efficiently capturing critical structural and chemical interactions efficiently. This study introduces amino acid pair position... read more 

Enhanced Sampling in the Age of Machine Learning: Algorithms and Applications.

Chemical reviews
Molecular dynamics simulations hold great promise for providing insight into the microscopic behavior of complex molecular systems. However, their effectiveness is often constrained by long timescales associated with rare events. Enhanced sampling me... read more 

Comparative Benchmark of Seven Large Language Models for Traumatic Dental Injury Knowledge.

European journal of dentistry
OBJECTIVES: Traumatic dental injuries (TDIs) are complex clinical conditions that require timely and accurate decision-making. With the rise of large language models (LLMs), there is growing interest in their potential to support dental management. T... read more 

Development of a Machine Learning-Based Predictive Model for Anastomotic Leakage Following Gastric Cancer Surgery.

The American surgeon
BackgroundThe incidence of anastomotic leakage (AL) following radical gastrectomy for gastric cancer ranges from 2.1% to 14.6%, with mortality rates up to 50%. Existing predictive methods lack both timeliness and accuracy. This study aimed to develop... read more 

Balancing Bias and Variance in Deep Learning-Based Tumor Microstructural Parameter Mapping.

Magnetic resonance in medicine
PURPOSE: Time-dependent diffusion MRI enables quantification of tumor microstructural parameters useful for diagnosis and prognosis. Nevertheless, current model fitting approaches exhibit suboptimal bias-variance trade-offs; specifically, nonlinear l... read more 

Physics-informed deep learning sharpens nano diagnostics for elusive pancreatic cancer.

Seminars in oncology
Pancreatic disease affects over 10% of the world population, and the most dangerous is pancreatic cancer (PC). The disease is mostly of late age of onset, especially in developed countries, and is associated with poor prognosis due to late presentati... read more 

From growing pains to growing evidence: a 2025 update on novel insights in lower limb osteochondroses.

Current opinion in pediatrics
PURPOSE OF REVIEW: Osteochondrosis encompasses a heterogenous group of pathologies affecting endochondral ossification in the growing child and adolescent. The cause of each disease is multifactorial, though many are often related to overuse injury, ... read more