AI Medical Compendium

Harnessing artificial intelligence for the assessment of liver fibrosis and steatosis via multiparametric ultrasound.

World journal of gastroenterology Jan 14, 2026

Artificial intelligence (AI) is revolutionizing medical imaging, particularly in chronic liver diseases assessment. AI technologies, including machine learning and deep learning, are increasingly integrated with multiparametric ultrasound (US) techni... read more

Development and deployment of an interpretable stacking ensemble model for predicting in-hospital mortality in ICU patients with chronic kidney disease and sepsis.

Digital health Jan 14, 2026

OBJECTIVE: To develop an interpretable stacking ensemble model for predicting in-hospital mortality in intensive care unit (ICU) patients with CKD and sepsis and to deploy it as a web-based tool for bedside clinical use. METHODS: Data were extracted ... read more

Single-inspiratory quantitative CT nomogram for enhanced PRISm and COPD differentiation: a cross-sectional study with interpretable diagnostic boundaries.

PeerJ Jan 14, 2026

BACKGROUND: Differentiating preserved ratio impaired spirometry (PRISm) from chronic obstructive pulmonary disease (COPD) is challenging. Traditional biphasic CT scans are limited by radiation exposure, while single-inspiratory CT-based deep learning... read more

Distinct neural signatures in a sensorimotor synchronization-continuation task.

Imaging neuroscience (Cambridge, Mass.) Jan 14, 2026

Optimal sensorimotor timing hinges on the generation, refinement, and employment of internal models to meet task demands. In finger tapping sensorimotor synchronization tasks, this occurs across and within tapping conditions that prompt externally-cu... read more

Predictors of past 30-day vaping abstinence among young e-cigarette users: Machine learning analysis of a longitudinal cohort.

Addictive behaviors Jan 14, 2026

INTRODUCTION: Our existing knowledge on factors influencing vaping abstinence are still limited. The objective of this study was to build a machine learning (ML)-based model to predict past 30-day vaping abstinence and identify predictors among young... read more

Ultrashort echo time MRI radiomics as a predictor of clinical outcomes in patellar tendinopathy: Insights from a large prospective clinical trial.

European journal of radiology Jan 14, 2026

PURPOSE: To evaluate the predictive utility of radiomic features extracted from ultrashort echo time (UTE) MRI in comparison to conventional proton density (PD) sequences for short-term (24-week) and long-term (5-year) clinical outcomes in patients w... read more

Volatile methyl siloxanes in electric vehicle cabin air: The first investigation of occurrence, influencing factors, and inhalation risks.

Journal of hazardous materials Jan 14, 2026

Volatile methyl siloxanes (VMS) are synthetic chemicals extensively used in various components of electric vehicles (EVs). However, their release characteristics in EV cabins and the potential inhalation risks to occupants remain unclear. This study ... read more

Modeling multidrug resistance in Campylobacter coli and Campylobacter jejuni isolated from swine at U.S. slaughter plants.

International journal of food microbiology Jan 14, 2026

Antimicrobial-resistant and multidrug-resistant Campylobacter spp. poses a human health risk. A total of 1694 isolates from market hogs (1599 Campylobacter coli and 95 C. jejuni) and 965 isolates from sows (918 C. coli and 47 C. jejuni) that were iso... read more

TransGAT-DTA: A multi-task framework for drug-target affinity prediction and conditional molecule generation.

Biochemical and biophysical research communications Jan 14, 2026

Discovering novel molecules that effectively interact with target proteins remains a time-consuming and costly challenge in drug development. Current machine learning approaches are typically limited to single-task settings and cannot simultaneously ... read more

The effectiveness of AI-based conversational agents in nursing education: A systematic review.

Nurse education in practice Jan 14, 2026

AIM: Comprehensive evaluation of randomized and non-randomized controlled trials (RCTs and NRCTs, respectively) on the effectiveness of AI-driven conversational agents in nursing education. BACKGROUND: AI-based conversational agents are innovative ed... read more

Artificial Intelligence Medical Compendium