AI Medical Compendium

Applications of machine learning in the diagnosis of non-alcoholic fatty liver disease: a systematic review and meta-analysis.

BMC gastroenterology Jun 3, 2026

OBJECTIVE: To systematically evaluate and quantify the diagnostic accuracy and performance of machine ML techniques for the detection of NAFLD, and to compare the performance of ML when assisting different diagnostic modalities, in order to provide t... read more

Utility of deep learning for degree calculation of aortic arch calcification in chest-X ray.

BMC medical imaging Jun 3, 2026

BACKGROUND: Aortic arch calcification (AoAC) is commonly classified into four grades according to the percentage of calcification observed in clinical practice, and the interpretation is typically based on visual assessment by clinicians. However, th... read more

Knowledge-guided brain tumor segmentation via synchronized visual-semantic-topological prior fusion.

BMC medical imaging Jun 3, 2026

Brain tumor segmentation requires precise delineation of hierarchical structures from multi-sequence MRI. However, existing deep learning methods primarily rely on visual features, showing insufficient discriminative power in ambiguous boundary regio... read more

SeqBoost: a sequential explainable model for predicting ED revisits within 72 hours.

BMC medical informatics and decision making Jun 3, 2026

PURPOSE: Accurately predicting emergency department (ED) revisits within 72 hours remains challenging due to irregular and short patient visit histories. This study investigates how temporal representations of historical ED utilization and sequential... read more

A systematic review of machine learning algorithms for mortality risk, readmission and phenotype prediction in patients with heart failure: exploring key data sources, input variables and outcomes.

BMC medical informatics and decision making Jun 3, 2026

BACKGROUND: Heart failure is not only a prevalent disease with a high mortality rate, but also generates high costs for healthcare systems. By training artificial intelligence (AI) models on medical data, it is possible to predict changes in health s... read more

Assessment of various artificial intelligence applications' performance in responding to multiple-choice endodontics questions.

BMC oral health Jun 3, 2026

BACKGROUND: Artificial intelligence (AI) has emerged as a transformative technology in the domain of healthcare, including endodontics. This study aims to evaluate and compare the performance of six AI chatbots (ScholarGPT, Scholar AI, ChatGPT-4o, Ge... read more

Accurate prediction of mortality in children with sepsis: development and validation of an explainable model based on real-world data.

Italian journal of pediatrics Jun 3, 2026

BACKGROUND: Sepsis remains the leading cause of in-hospital deaths among children, and there is currently a lack of precise early prediction models. This study aimed to develop an interpretable machine learning (IML) model to predict in-hospital mort... read more

PepPharmaHub: a cloud-based platform integrating multimodel language architectures with curated data resources for therapeutic peptide discovery.

BMC biology Jun 3, 2026

BACKGROUND: Therapeutic peptides represent a rapidly expanding class of drug candidates due to their diverse biological activities and high specificity. However, accurately predicting peptide functions directly from sequence information remains a maj... read more

Clinical Applicability of Artificial Intelligence-Driven Implant Planning and Surgical Guide Design in the Maxillary Esthetic Zone: A Registry-Based Cohort Study.

Clinical oral implants research Jun 3, 2026

OBJECTIVES: This study evaluated the accuracy, time efficiency, and workflow consistency of artificial intelligence (AI)-assisted versus human expert (HI) implant planning in the esthetic anterior maxilla. MATERIAL AND METHODS: Thirty-five single-too... read more

Multi-omics biomarkers in endometrial receptivity: from mechanisms to clinical translation.

Journal of translational medicine Jun 3, 2026

BACKGROUND: Endometrial receptivity (ER) serves as a critical determinant for successful embryo implantation, yet its molecular complexity and limited clinical assessment methods pose significant challenges. Despite advancements in assisted reproduct... read more

Artificial Intelligence Medical Compendium