Artificial Intelligence Medical Compendium

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

Showing 7,181 to 7,190 of 206,272 articles

Clinically oriented deep learning system integrating linear and morphological assessment for external orthodontic root resorption.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics Jun 1, 2026
INTRODUCTION: Manual linear assessment, a classic method for evaluating orthodontic external root resorption (OERR), has limitations: unreliable dento-osseous junction identification and operator variability, time-consuming measurements, and inabilit... read more 

Evaluation of Clinically-Focused Artificial Intelligence Chatbots for Answering Drug Information Questions.

Journal of the American College of Clinical Pharmacy : JACCP Jun 1, 2026
BACKGROUND: Artificial intelligence (AI) tools are increasingly promoted for clinical decision support in health care. While studies have assessed general-purpose AI chatbots on the accuracy and quality of clinical or drug-related questions, direct c... read more 

Artificial Intelligence for Invasion-Depth Prediction in Colorectal Cancer: From Technical Promise to Clinically Credible Support.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society Jun 1, 2026
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Artificial Intelligence-Based Objective Evaluation of Nerve-Sparing Status Combined With Preserved Urethral Length Predicts Urinary Continence Recovery After Robot-Assisted Radical Prostatectomy.

International journal of urology : official journal of the Japanese Urological Association Jun 1, 2026
OBJECTIVES: To evaluate nerve-sparing status objectively using an artificial intelligence method applied to intraoperative images and to determine whether combining this assessment with preserved urethral length improves prediction of urinary contine... read more 

High-frequency EEG synchronization modes as a stable biometric signature in humans.

iScience Jun 1, 2026
Electroencephalography (EEG) offers a promising modality for biometric identification, though balancing performance, interpretability, and robustness remains a challenge. High-accuracy methods typically rely on supervised or deep learning models with... read more 

Integrating MIKE model simulations with CNNs for rapid and accurate urban flood prediction.

iScience Jun 1, 2026
Rapid prediction of urban pluvial flooding is an important tool for mitigating current urban flooding disasters. This paper constructs a fast prediction model for urban flooding based on a machine learning approach. Firstly, MIKE numerical model simu... read more 

Mental health in early pregnancy: Interplay of objectively measured lifestyles, gut microbiota, and metabolomics.

iScience Jun 1, 2026
Prenatal anxiety symptoms (AS) and depression symptoms (DS) in early pregnancy substantially impact maternal-infant health, but their pathophysiological mechanisms remain unclear. We conducted a multimodal assessment of 161 early-pregnant women. DS e... read more 

Social Reasoning-Aware Trajectory Prediction via Multimodal Language Model.

IEEE transactions on pattern analysis and machine intelligence Jun 1, 2026
Recent advancements in language models have demonstrated its capacity of context understanding and generative representations. Leveraged by these developments, we propose a novel multimodal trajectory predictor based on a vision-language model, named... read more 

Characterizing Central-Autonomic Dynamics During an Episodic Memory Task Using Multi-Modal Neural and Cardiomechanical Signals.

IEEE transactions on bio-medical engineering Jun 1, 2026
OBJECTIVE: Memory function underlies mental and behavioral health. While the role of the central nervous system (CNS) during episodic memory encoding and retrieval is well researched, the interplay between the CNS and the autonomic nervous system (AN... read more 

Direct Quantification of Uncertainty in Deep Learning-Based Automatic Sleep Staging.

IEEE transactions on bio-medical engineering Jun 1, 2026
OBJECTIVE: To evaluate and compare different methods for quantifying uncertainty in deep learning-based automatic sleep staging, thereby enhancing transparency and supporting clinical adoption. METHODS: Three models trained on the STAGES dataset were... read more 
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