Artificial Intelligence Medical Compendium

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

Showing 9,461 to 9,470 of 208,566 articles

Epigenetic precision diagnostics of traditional Chinese medicine (TCM) syndrome differentiation: a pilot study of atrial fibrillation with qi-yin deficiency syndrome based on 5-hydroxymethylcytosine signatures in extracellular vesicle DNA from plasma.

Chinese medicine
BACKGROUND: Syndrome differentiation in Traditional Chinese Medicine (TCM) is pivotal to clinical practice and dictates the efficacy of medicinal treatments. However, precision diagnostic models for TCM syndromes, constructed from biomarkers such as ... read more 

Frequency- and Network-Specific Changes in Functional Connectivity Reflect Pathophysiological Mechanisms across Parkinson's Disease Stages.

Annals of neurology
OBJECTIVE: Parkinson's disease (PD) is increasingly conceptualized as a disorder of large-scale brain networks, yet whether and how frequency-specific functional connectivity reorganizes across stages remains poorly understood. In this study, we used... read more 

Using artificial intelligence-assisted retinal imaging devices operated by non-specialist workers in detecting diabetic retinopathy in Sri Lanka.

BMC global and public health
BACKGROUND: Diabetic retinopathy (DR), a microvascular complication of diabetes, is an important cause of preventable blindness and can cause a significant reduction in the quality of life of working-age adults. Sri Lanka has one of the highest preva... read more 

Machine-learning-model based tool for screening bone metastases from lung cancer patients in primary care practice.

Journal of orthopaedic surgery and research
PURPOSE: This study aimed to use the machine-learning methods to predict bone metastasis (BM) in patients with lung cancer. METHODS: This study included 8,612 patients with lung cancer, from whom we collected baseline characteristics and hematologica... read more 

Dual inhibition of KDM4B and KDM5A disassembles the PAX3-FOXO1 transcriptional program in fusion-positive rhabdomyosarcoma.

Biology direct
BACKGROUND: Fusion-positive rhabdomyosarcoma (FP-RMS) is driven by the oncogenic transcription factor PAX3-FOXO1 and is associated with poor clinical outcome. The histone demethylase KDM4B has been implicated in sustaining PAX3-FOXO1-dependent transc... read more 

Unraveling EFL students' technology self-efficacy, emotions and behavioral intentions in leveraging large language models: the serial mediation of perceptions and attitudes.

BMC psychology
With the growing momentum to integrate artificial intelligence (AI) into education, large language models (LLMs) have shown great potential for English as a Foreign Language (EFL) learning. However, the relationships between EFL students' technology ... read more 

Quality and performance of machine learning versus logistic regression for predicting IVIG resistance in Kawasaki disease: a PROBAST+AI systematic comparison.

BMC medical research methodology
BACKGROUND: This study aimed to systematically compare the predictive performance and methodological quality of logistic regression (LR) and machine learning (ML) models for intravenous immunoglobulin (IVIG) resistance in Kawasaki disease (KD) using ... read more 

Machine learning models for predicting metabolic syndrome to support clinical decision-making in ART-treated adults living with HIV.

BMC medical informatics and decision making
BACKGROUND: Metabolic syndrome (MetS) is an emerging complication among people living with HIV (PLHIV) receiving long-term antiretroviral therapy (ART), particularly with protease and integrase inhibitor regimens. Early identification of high-risk in... read more 

SPARK: making ethical and societal tensions explicit in AI-supported precision medicine education.

BMC medical ethics
BACKGROUND: Precision medicine is often framed in terms of technical innovation and clinical promise, while its broader ethical and societal implications receive less attention in medical training. Addressing these issues requires formats that allow ... read more 

Comparative efficacy of six contemporary large language models in prosthodontic patient education: a multi-parameter blinded assessment.

BMC oral health
BACKGROUND: This study aimed to evaluate and benchmark the proficiency of six major large language models (LLMs)-specifically the versions publicly available as of March 2025 (ChatGPT-4o, Claude 3.7 Sonnet, Microsoft Copilot, DeepSeek-V2, Gemini 2.0,... read more