Artificial Intelligence Medical Compendium

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

Showing 64,971 to 64,980 of 231,605 articles

Machine learning-guided identification of metastasis-associated miRNAs and their integration into a PFI-based cox risk score and nomogram.

Computers in biology and medicine Jan 11, 2026
BACKGROUND: Metastasis drives mortality in breast invasive carcinoma. We sought miRNA biomarkers that (i) discriminate metastatic potential, (ii) stratify prognosis, and (iii) translate into a clinically useful PFI predictor. METHODS: We analyzed 858... read more 

Muscle ultrasonography texture in young, middle-aged, and older people and its association with functional performance: A machine learning-based study.

Experimental gerontology Jan 11, 2026
BACKGROUND: Skeletal muscle deterioration accelerates with age, leading to muscle atrophy and dysfunction. Musculoskeletal ultrasound as a nonradiative, inexpensive, and portable tool, has potential to evaluate age-related muscle changes. This study ... read more 

Sequential viseme-driven visual speech recognition through dual-stream interactive neural architecture.

Neural networks : the official journal of the International Neural Network Society Jan 11, 2026
While achieving considerable success as a sequence-to-sequence prediction task, current deep neural network-based sentence-level lipreading methods exhibit a fundamental limitation: the preservation of overall semantics often comes at the expense of ... read more 

VENI, VINDy, VICI: A generative reduced-order modeling framework with uncertainty quantification.

Neural networks : the official journal of the International Neural Network Society Jan 11, 2026
Generative models are transforming science and engineering by enabling efficient synthetization and exploration of new scenarios for complex physical phenomena with minimal cost. Although they provide uncertainty-aware predictions to support decision... read more 

On scientific foundation models: Rigorous definitions, key applications, and a comprehensive survey.

Neural networks : the official journal of the International Neural Network Society Jan 11, 2026
Scientific Foundation Models (SciFMs) represent a transformative paradigm for addressing complex scientific and engineering problems by leveraging large-scale pretraining and deep learning architectures. Unlike traditional numerical solvers, which re... read more 

DMDNet: Dual-branch multi-modal deep fusion network for V-D-T salient object detection.

Neural networks : the official journal of the International Neural Network Society Jan 11, 2026
In the multi-modal salient object detection task, depth or thermal features are often directly fused with visible feature during the encoding stage, which directly results in the fused encoder features containing a large amount of noise information a... read more 

RoGAtten: Rotary gated linear attention for multivariate time series forecasting.

Neural networks : the official journal of the International Neural Network Society Jan 11, 2026
Thousands of network nodes in the Internet of Things produce vast amounts of long-term time series. Predicting network traffic helps identify security risks and improve network management. In the past few years, Transformer-based models (Transformers... read more 

A modern look at simplicity bias in image classification tasks.

Neural networks : the official journal of the International Neural Network Society Jan 11, 2026
Simplicity bias (SB), the tendency of neural networks to learn simpler functions, is a key factor in good generalization. Recent studies have examined SB mainly using simple models or easily controlled synthetic tasks. However, the effect of SB on ge... read more 

GCLSC: Single-cell clustering model based on graph contrastive learning.

Computational biology and chemistry Jan 11, 2026
The advent of single-cell RNA sequencing (scRNA-seq) technology has enabled the analysis of cellular heterogeneity at the single-cell level. In scRNA-seq data analysis, cell clustering is a crucial downstream task, as it facilitates the discovery of ... read more 

Rapid identification of Polygonatum kingianum processed by nine steaming and nine drying based on FT-NIR and ATR-FTIR combined with deep learning.

Talanta Jan 11, 2026
The nine-steaming and nine drying process is the traditional preparation method for Polygonatum sibiricum, involving repeated steaming and drying nine times to optimize its dual medicinal and edible value, making it the preferred technique. Though co... read more 
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