Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 44,191 to 44,200 of 224,055 articles

Climate predictors of child undernutrition: Insights from a machine learning model.

PloS one Mar 6, 2026
BACKGROUND: Climate variability is increasingly recognized as a driver of child undernutrition, yet the non-linear relationships between specific climatic variables and nutrition remain unclear. This study uses machine learning to identify and quanti... read more 

Engaging stakeholders, shaping AI ethics: Targeted engagement in corporate AI ethics statements.

PloS one Mar 6, 2026
Corporate AI ethics statements are being increasingly integrated into sustainability communication to showcase responsible AI performance as part of broader sustainable efforts. This study examines how leading AI companies (developers and adopters) e... read more 

Predictive divergence in machine learning models for clinical mortality risk: A multicohort study of covid-19 patients.

PloS one Mar 6, 2026
BACKGROUND: Machine learning (ML) algorithms are increasingly used in healthcare to support clinical decision-making. While models with similar overall performance are often considered interchangeable for deployment, they may produce divergent predic... read more 

Strategic SA-UNet: Integrating self-attention blocks into U-Net for efficient crack segmentation.

PloS one Mar 6, 2026
Accurate crack segmentation plays a crucial role in ensuring safety and mitigating disaster risks during road inspections and structural health monitoring. However, traditional image processing techniques often struggle with low detection accuracy an... read more 

Integrating contrastive cross-modal attention and stacked GRU for hand function rehabilitation robot control.

PloS one Mar 6, 2026
With the intensification of population aging and the increasing incidence of neurological diseases, the demand for precise and intelligent control technology in hand rehabilitation robots has become more urgent. Traditional control methods struggle t... read more 

MoGraphDRP: Multi-omics and graph fusion with bilinear attention for predicting drug sensitivity.

PloS one Mar 6, 2026
Accurate prediction of drug response in cancer cells is a fundamental step toward achieving precision medicine and designing personalized therapies. In this study, a multi-branch deep learning framework is proposed that integrates multi-omics cellula... read more 

A full belly counsels well: More stabilisation with more responsibility.

PloS one Mar 6, 2026
DESIGN/METHODOLOGY/APPROACH: This paper uses the data of Chinese A-share listed companies from 2009 to 2022 to study the impact of supply chain stability on corporate ESG performance. PURPOSE: To study the impact and mechanism of supply chain stabili... read more 

A 1D Snoring Waveform and 2D Composite Acoustic Feature Graph-Based Multi-Modal Fusion Network for Obstructive Sites Recognition.

IEEE journal of biomedical and health informatics Mar 6, 2026
As a critical factor in diagnostic work-up and treatment decision-making process of sleep-related breathing disorders, accurate localization of obstructive sites in the upper airway is in dire need. Snoring, as a dynamic acoustic signal, carries info... read more 

Global Polynomial Synchronization of Uncertain Complex-Valued Reaction-Diffusion T-S Fuzzy Memristive Neural Networks With Proportional Delays Under Adaptive Event-Triggered Control.

IEEE transactions on neural networks and learning systems Mar 6, 2026
This article addresses global polynomial synchronization (GPS) for uncertain complex-valued reaction-diffusion Takagi-Sugeno (T-S) fuzzy memristive neural networks (MNNs) with proportional delays. First, the interval matrix theory is extended, for th... read more 

Rederived Closed-Form Continuous-Time Neural Networks.

IEEE transactions on neural networks and learning systems Mar 6, 2026
In the field of machine learning, continuous-time neural networks (CTNNs) have garnered significant attention due to their powerful modeling capabilities for time series data. However, traditional numerical ordinary differential equation (ODE) solvin... read more 
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