AI Medical Compendium

OLink proteomic biomarker to predict clinical efficacy of Macaranga sinensis Müll.Arg: A nested case-control study.

Journal of ethnopharmacology Jan 18, 2026

ETHNOPHARMACOLOGICAL RELEVANCE: Despite the fact that herbal medicine has been used for a long time, their clinical application is challenged by unclear active ingredients and poorly understood mechanisms of action, resulting in considerable heteroge... read more

Construction of musculoskeletal quantitative model based on deep learning and study of musculoskeletal relationship in patients with osteoporosis.

Journal of advanced research Jan 18, 2026

INTRODUCTION: Lumbar CT and MRI scans are helpful for osteoporosis (OP) screening. Deep learning enhances the efficiency and accuracy of musculoskeletal quantification for OP screening. OBJECTIVES: To develop a deep learning-based model (UNet3D) for ... read more

Controlling gene expression using AI designed Cis-regulatory elements.

Biotechnology advances Jan 18, 2026

Cis-regulatory elements (CREs) play a crucial role in regulating gene expression by controlling transcription, making the understanding and design of these elements essential for the advancement of biology. Traditional approaches often rely on empiri... read more

Machine learning based prediction of mechanical properties in carbon fiber recovered through pyrolysis.

Waste management (New York, N.Y.) Jan 18, 2026

The limitations of traditional pyrolysis technologies of recovered carbon fiber included long processing time, low efficiency, and unclear links between process parameters and performance. Moreover, pyrolysis alone formed residual coke on carbon fibe... read more

SERS-enabled immune monitoring: Decoding the tumor microenvironment for precision Cancer immunotherapy.

International immunopharmacology Jan 18, 2026

The tumor immune microenvironment (TME) is pivotal in regulating cancer initiation, progression, and therapeutic response. Despite major advances in immunotherapy, clinical outcomes remain limited by low response rates and unpredictable immune-relate... 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

Artificial Intelligence Medical Compendium