AI Medical Compendium

Admission blood pressure percentiles and in-hospital mortality in pediatric heart failure: a multicenter retrospective cohort study.

World journal of pediatrics : WJP May 15, 2026

BACKGROUND: Pediatric heart failure (PHF) carries a high mortality burden, yet the prognostic value of admission blood pressure (BP) remains poorly defined, and evidence-based thresholds for risk stratification are lacking. METHODS: This retrospectiv... read more

Leveraging artificial intelligence to predict non-adherence to pediatric immunization schedules: a systematic review.

European journal of pediatrics May 15, 2026

UNLABELLED: Immunization is one of the most effective interventions to prevent infectious diseases. Identifying individuals at risk of non-adherence to immunization schedules could enable early interventions to improve coverage. With the increasing a... read more

Concordance of Large Language Model Recommendations with Multidisciplinary Heart Team Decisions in Coronary Revascularization and Aortic Valve Intervention: A Systematic Review and Pooled Analysis.

Cardiology and therapy May 15, 2026

INTRODUCTION: The multidisciplinary heart team (HT) remains the cornerstone of decision-making for complex cardiovascular disease. Large language models (LLMs) and other generative artificial intelligence models have recently emerged as potential dec... read more

Interpretable machine learning model integrating MRI-derived paraspinal muscle parameters for predicting new vertebral compression fractures after vertebral augmentation.

European radiology May 15, 2026

OBJECTIVES: To develop and validate interpretable machine learning (ML) models incorporating MRI-derived paraspinal muscle parameters to predict new vertebral compression fractures (NVCF) after vertebral augmentation. MATERIALS AND METHODS: This mult... read more

Development and validation of an explainable machine learning model using routine laboratory biomarkers for identifying prevalent MASLD: Evidence from two observational studies.

Clinical and experimental medicine May 15, 2026

Although many predictive models for metabolic dysfunction-associated steatotic liver disease (MASLD) have been developed, their performance remains suboptimal. We aimed to develop an interpretable machine learning (ML)-based plasma biomarker model fo... read more

HESpotEx: a dual-stream deep learning framework for spot-level gene expression prediction from histological images.

Nature computational science May 15, 2026

Whole-slide histopathological images (WSIs) constitute a fundamental approach in disease diagnosis and prognosis. Recently emerging spatial transcriptomics (ST) methods can reveal the spatial gene expression landscape behind the histopathological ima... read more

MRI- and report-based multimodal model with SHAP-based explanation for preoperative prediction of deep stromal invasion in early-stage cervical cancer.

Insights into imaging May 15, 2026

OBJECTIVES: Depth of stromal invasion (DSI) is a key prognostic factor significantly influencing treatment decisions in early-stage cervical cancer (ESCC). This study aims to develop an explainable multimodal data fusion model integrating MRI, radiol... read more

Machine-Learning-Based Prediction of Long-Term Efficacy of Nemolizumab: Post Hoc Analysis of Pooled Data from Two Phase III Clinical Trials.

Dermatology and therapy May 15, 2026

INTRODUCTION: Nemolizumab is a humanized monoclonal antibody that specifically inhibits the receptor for interleukin-31, the major pruritogen in atopic dermatitis (AD). While the patient profile associated with the early therapeutic response to nemol... read more

Metabolomics at the Crossroads of Forensic Toxicology and Precision Diagnostics: Analytical Innovations and Translational Opportunities.

Omics : a journal of integrative biology May 15, 2026

Metabolomics is the comprehensive analysis of small-molecule metabolites in living systems and is increasingly being applied in forensic science and health diagnostics. This review broadly integrates the foundational principles of metabolomics, key a... read more

Noninvasive early detection and grading of pneumoconiosis via plasma proteomics and machine learning: PRSS3 as a potential biomarker.

Clinical proteomics May 15, 2026

BACKGROUND: Coal-dust, a persistent airborne pollutant, induces dose-related pulmonary fibrosis; however, plasma biomarkers for pre-clinical toxicity remain lacking. METHODS: We enrolled 158 participants, including 28 healthy controls (HCs), 30 dust-... read more

Artificial Intelligence Medical Compendium