AI Medical Compendium

[Chapter 4. Neurotechnologies: striking a balance between scientific progress and privacy].

Journal international de bioethique et d'ethique des sciences May 7, 2026

Neurotechnologies encompass a wide range of devices, from EEGs to neural interfaces, used for therapeutic, diagnostic, or research purposes. These technologies collect valuable but highly intimate and identifying brain data, which feeds into internat... read more

Machine learning the order-disorder Jahn-Teller transition in LaMnO3.

The Journal of chemical physics May 7, 2026

We investigate the Jahn-Teller structural phase transition in LaMnO3 at TJT ≃ 750 K using molecular dynamics simulations based on machine-learning force fields trained on ab initio data. Analysis of the site-site correlation function of the distortio... read more

Integrating quantum neural networks with the variational quantum eigensolver to calculate nonadiabatic coupling vectors.

The Journal of chemical physics May 7, 2026

Machine learning nonadiabatic coupling vectors (NACVs) is challenging due to the localized value problem and the sign problem. In this study, we integrate quantum neural networks (QNNs) with the variational quantum eigensolver (VQE) to predict NACVs ... read more

Opportunities for deep learning techniques to advance the histological analysis of preclinical models of osteoarthritis beyond ordinal rank systems.

JBMR plus May 7, 2026

Tools for assessing disease progression are needed to identify and confirm new mechanisms driving osteoarthritis (OA) progression and guide therapeutic development. This review focuses on the advantages and feasibility of leveraging deep learning tec... read more

Development and validation of a clinlabomics-based machine-learning model for noninvasive risk stratification of moderate-to-severe OSA.

International journal of medical informatics May 7, 2026

PURPOSE: Obstructive sleep apnea (OSA) is a highly prevalent sleep disorder strongly associated with adverse cardiometabolic and neurocognitive outcomes. Polysomnography (PSG), the diagnostic gold standard, is not a readily accessible test. Therefore... read more

Unveiling the drivers of groundwater quality in an industrial plain: An integrated hydrogeochemical and stacking ensemble learning approach.

Journal of contaminant hydrology May 7, 2026

Understanding the hydrochemical evolution and primary chemical components governing groundwater quality in industrial regions is crucial for sustainable groundwater management. This study established an integrated analytical framework by combining co... read more

RNA-based cancer immunotherapy: Harnessing the power of RNA nanoparticles for melanoma treatment.

Pathology, research and practice May 7, 2026

RNA-based cancer immunotherapy has emerged as a next-generation strategy in oncology, harnessing the versatile properties of RNA molecules to activate and modulate antitumor immunity. In melanoma, a highly immunogenic yet evasive malignancy, RNA ther... read more

Radiomics and deep learning models for predicting glioma p53 status: A diagnostic accuracy systematic review and meta-analysis of magnetic resonance imaging studies.

Clinical imaging May 7, 2026

PURPOSE: To systematically investigate the diagnostic performance of magnetic resonance imaging (MRI)-based radiomics and deep learning (DL) models for predicting p53 status in glioma and to generate pooled estimates for radiomics-based models. METHO... read more

Improved water quality assessment and prediction for small watersheds in human settlements of the Chengdu plain, southwestern China.

Journal of contaminant hydrology May 7, 2026

Water is a critical natural resource for maintaining the stability of Earth's ecosystems and the sustainable development of human society and economy. As the basic unit of terrestrial hydrological cycles, small watersheds have water quality condition... read more

Identifying pre-treatment risk factors for cancer-related cognitive decline in patients with breast cancer.

Breast (Edinburgh, Scotland) May 7, 2026

PURPOSE: To explore pre-treatment risk factors for cognitive decline in patients with breast cancer using a machine learning approach applied to a comprehensive multimodal clinical, biological, and neuroimaging dataset. METHODS: Sixty-seven women wit... read more

Artificial Intelligence Medical Compendium