AI Medical Compendium

Interpretable machine learning model for predicting in-hospital mortality in elderly acute pancreatitis: Development and validation in a multicenter cohort.

International journal of medical informatics Jan 18, 2026

BACKGROUND: Elderly acute pancreatitis (AP) patients face significantly higher in-hospital all-cause mortality, highlighting the need for effective risk stratification to support timely clinical decision-making. METHODS: We conducted a multicenter re... read more

Clinician preferences for explainable AI in critical care: a comparative study of interpretable models and visualizations for intubation decision support.

International journal of medical informatics Jan 18, 2026

BACKGROUND: The complexity of many AI models hinders their clinical adoption because the clinicians using them do not regard them as transparent. This study addresses the lack of clinician-centered explainable AI (XAI) interfaces by designing and eva... read more

Regression augmentation with data-driven segmentation.

Neural networks : the official journal of the International Neural Network Society Jan 18, 2026

Imbalanced regression arises when the target distribution is skewed, causing models, especially neural networks, to focus on dense regions and struggle with underrepresented (minority) samples. Despite its relevance across many applications, few meth... read more

Clinical validation of a unified data-driven respiratory motion correction technique in 18F-FDG PET/CT imaging of upper abdominal lesions: a real-world study.

EJNMMI physics Jan 18, 2026

PURPOSE: Respiratory motion (RM)-related artifacts significantly impact image quality and diagnostic accuracy in PET/CT imaging. This study aimed to prospectively evaluate the clinical utility of the unified data-driven respiratory motion correction ... read more

Insights into the interplay between stroke and depression through lipid metabolism-related diagnostic genes.

Molecular brain Jan 18, 2026

Stroke, a result of acute cerebrovascular disease that causes cerebral dysfunction, often coexists with depression or even major depressive disorder (MDD). Despite the recognized significance of lipid metabolism disorders in both stroke and depressio... read more

Small Models Achieve Large Language Model Performance: Evaluating Reasoning-Enabled AI for Secure Child Welfare Research.

Journal of evidence-based social work (2019) Jan 18, 2026

PURPOSE: This study develops a systematic benchmarking framework for testing whether language models can accurately identify constructs of interest in child welfare records. The objective is to assess how different model sizes and architectures perfo... read more

Restraint Quality, Not Quantity, Predicts Peptide-Protein Docking Outcomes.

Journal of chemical information and modeling Jan 18, 2026

Understanding protein-peptide interactions is essential for uncovering cellular signaling mechanisms and advancing therapeutic development, as these interactions play central roles in numerous biological processes. Gaining structural insight into suc... read more

Deciphering the molecular landscape of Sjögren's disease, mucosa-associated lymphoid tissue lymphoma, and thyroid cancer: unraveling the complexities of disease mechanisms and diagnostic biomarkers.

Clinical rheumatology Jan 18, 2026

BACKGROUND: Sjögren's disease (SjD), mucosa-associated lymphoid tissue lymphoma (MALT lymphoma), and thyroid cancer (THCA) are clinically distinct yet immunologically intertwined diseases characterized by chronic inflammation and aberrant immune acti... read more

Continuous Glucose Monitoring-Based Machine Learning Identification of Diurnal Glycemic Patterns and Diabetes Distress in Type 2 Diabetes.

Journal of diabetes science and technology Jan 18, 2026

BACKGROUND: To identify diurnal glycemic patterns in adults with type 2 diabetes (T2D) using continuous glucose monitoring (CGM)-based machine learning and examine their association with diabetes distress, a key psychosocial outcome. METHODS: In this... read more

Efficacy of an AI-Enabled Low Glucose Prediction: A Pooled Performance Analysis With Capillary Blood Glucose as Ground Truth.