AI Medical Compendium

Deep learning-based automated segmentation and quantification of aortic arch calcification at chest radiograph.

BMC geriatrics May 11, 2026

BACKGROUND: Aortic arch calcification (AoAC) is an established independent predictor of coronary heart disease and broader cardiovascular outcomes. We have developed a deep convolutional neural network that enables automated detection and quantificat... read more

Machine learning-based prediction of diabetic retinopathy using clinlabomics: a multi-center study.

BMC medical informatics and decision making May 11, 2026

BACKGROUND: Diabetic retinopathy (DR) is a leading cause of vision loss, yet conventional retinal screening remains costly and resource-intensive. This study developed and validated machine-learning (ML) models using routine laboratory data to provid... read more

Involved nodal versus elective neck radiotherapy (INVERT) for head and neck squamous cell carcinoma: a prospective phase II randomized controlled trial protocol.

BMC cancer May 11, 2026

BACKGROUND: Definitive chemoradiotherapy for head and neck squamous cell carcinomas (HNSCC) carries significant long-term toxicities, with elective neck irradiation (ENI) serving as a major contributor to integral dose and the irradiation of critical... read more

A TyG-UHR-based machine learning model for screening lean MAFLD: development and external validation.

Biomedical engineering online May 11, 2026

BACKGROUND: Lean metabolic dysfunction-associated fatty liver disease (MAFLD) is increasingly recognized but often goes unnoticed during health checkups and primary care due to low perceived risk and limitations of imaging. Cost-effective, automated ... read more

Harnessing meta-analysis and artificial intelligence to reveal conserved regulatory biosignatures of abiotic stress in soybean.

Biology direct May 11, 2026

BACKGROUND: Soybeans are widely cultivated worldwide as an important source of edible vegetable oil and protein. Due to climate change, it is repeatedly exposed to various abiotic stressors in its natural habitat. Abiotic stresses such as heat, droug... read more

The conditional indirect effect of perceived robot threat on employees' proactive behavior: the moderating role of human-robot interaction.

BMC psychology May 11, 2026

In the era of artificial intelligence, an increasing number of robots are entering the workplace as active contributors to organizational tasks. While robots can enhance employees' efficiency by complementing human capabilities, they may also lead to... read more

Clinical-ShiftEval: a framework for simulating and evaluating model adaptation in dynamic clinical NLP tasks.

BMC medical informatics and decision making May 11, 2026

BACKGROUND: Clinical natural language processing (NLP) models are widely used to extract information from electronic health records (EHR) and support healthcare decision-making. However, most existing models are evaluated under the assumption of stat... read more

WBT-DC pipeline: a cross-cohort and cross-platform disease classification pipeline based on whole-blood transcriptomics.

Journal of translational medicine May 11, 2026

BACKGROUND: Machine-learning models based on tissue transcriptomic data are powerful tools for disease classification. However, their clinical adoption is limited by the invasive nature of tissue sampling. Furthermore, transcriptomic datasets are oft... read more

De novo design of anticancer 4-thiazolidinone derivatives: a generative framework shaped by activity cliffs.

Journal of cheminformatics May 11, 2026

Activity cliffs (AC) correspond to large potency differences between highly similar compounds and pose a persistent challenge for both predictive modeling and de novo molecular design, particularly in small and underexplored areas of the chemical spa... read more

Adaptive drift-aware multi-stage deep learning framework for EEG-based schizophrenia diagnosis.

BioData mining May 11, 2026

This study introduces a novel adaptive deep learning framework for EEG-based schizophrenia diagnosis that addresses the limitations of existing static classification models. Traditional approaches often fail to maintain diagnostic reliability when EE... read more

Artificial Intelligence Medical Compendium