AI Medical Compendium

Machine learning-based prognostic model integrating preoperative HALP score and lactate dehydrogenase for predicting postoperative recurrence of prostate cancer.

World journal of surgical oncology May 27, 2026

OBJECTIVE: Postoperative biochemical recurrence (BCR) of prostate cancer (PCa) remains a major clinical challenge, and traditional risk assessment systems show suboptimal predictive performance for PCa recurrence. This study aimed to develop and vali... read more

The AI inversion model: a linear negative-constraint framework for auditable alignment in medical decision-making.

BMC medical ethics May 27, 2026

The integration of artificial intelligence (AI) into healthcare systems is increasingly hindered by the AI alignment problem. In high-stakes domains such as clinical triage, algorithms frequently reflect and amplify systemic biases. Current alignment... read more

Development and validation of the Dental Artificial Intelligence Readiness and Acceptance Instrument (DAI-RAI) for dental professionals.

BMC oral health May 27, 2026

BACKGROUND: Artificial intelligence (AI), including applications such as radiographic image analysis, caries detection, and treatment planning, is increasingly integrated into dental diagnostics, education, and clinical workflows. However, validated ... read more

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 May 27, 2026

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 May 27, 2026

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 May 27, 2026

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 May 27, 2026

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 May 27, 2026

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 May 27, 2026

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 May 27, 2026

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

Artificial Intelligence Medical Compendium