AI Medical Compendium

Natural biowaste material-based green triboelectric nanogenerators for self-powered gait monitoring.

RSC advances Jan 14, 2026

The advancement of triboelectric nanogenerators (TENGs) has attracted increasing interest in recent years due to the growing tension between the increasing demand for energy and the increasing destruction of fossil fuels. For environmentally friendly... read more

Automated Learning of a Dense Manifold of Electronic States and Electronic Energy Transfer and Reactions in Singlet O Collisions with N2.

Research (Washington, D.C.) Jan 14, 2026

Calculations of collisions involving excited electronic states play an important role in many high-energy environments, for example, in simulating thermal energy content and heat flux in flows around hypersonic reentry vehicles, and useful data are u... read more

Web-Based Sustainable Detection and Treatment Recommendation System for Wheat Plant Diseases Using Convolutional Neural Networks.

Food science & nutrition Jan 14, 2026

Wheat, being a major staple crop worldwide, is often attacked by rust diseases, which cause severe yield losses. The early detection and diagnosis of fungal infections, yellow rust, and brown rust are critical in minimizing their consequences. A web-... read more

Machine learning identifies proteomic risk factors across 23 diseases.

iScience Jan 14, 2026

Achieving minimally invasive and rapid detection is a crucial goal in modern medicine. The comprehensive characterization of the blood proteome holds great promise in advancing our understanding of disease etiology, facilitating early diagnosis, risk... read more

Relationship between resource utilization and diagnostic accuracy of large language models for efficient multimodal reasoning in radiologic image interpretation.

European journal of radiology Jan 14, 2026

OBJECTIVES: We evaluated the diagnostic performance and resource efficiency of three multimodal-reasoning-models for radiological image interpretation. METHODS: Using three multimodal-reasoning-models, we analyzed 73 cases under different conditions ... read more

Identification of novel umami peptides in fermented milk and elucidation of their umami mechanism via molecular docking and molecular dynamics simulations.

Food chemistry Jan 14, 2026

A streamlined workflow integrating multi-model machine learning, bioinformatics filtering, sensory evaluation, molecular docking and dynamics simulations was applied to mine umami peptides in fermented milk. Based on dual selection criteria-(i) unani... read more

Robust multimodal mental workload classification: A cross-physiological condition machine learning approach.

Computer methods and programs in biomedicine Jan 14, 2026

BACKGROUND AND OBJECTIVE: Aircraft pilots can be faced with a high mental workload (MW) combined with moderate hypoxia and sleep restriction. We aimed to assess the cross-validation of a machine learning-based MW predictive model under hypoxia and/or... read more

An adaptive machine learning framework integrating large language models to assess and enhance emotional intelligence in adolescents.

Asian journal of psychiatry Jan 14, 2026

BACKGROUND: Emotional intelligence (EI) is a critical determinant of children's socio-emotional and neurocognitive development, and deficits in EI dimensions are associated with long-term psychological and behavioral risks. Existing interventions are... read more

Predicting curcumin release kinetics from nanocarriers using a physics-informed machine learning framework.

Computational biology and chemistry Jan 14, 2026

BACKGROUND: Curcumin nanoformulations display highly heterogeneous release behaviors, yet the field lacks an integrated framework capable of predicting kinetics across diverse material classes. However, the diffusion parameters governing these system... read more

Performance analysis of liver segmentation using nn-UNet TotalSegmentator: Focus on atypical livers, pathologies, and variants.