Artificial Intelligence Medical Compendium

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

Showing 65,271 to 65,280 of 231,904 articles

P300-based support vector machine model for identifying adolescent with first-episode, drug-naïve major depressive disorder.

Journal of affective disorders Jan 11, 2026
BACKGROUND: Major depressive disorder (MDD) is diagnosed mainly through clinical interviews, highlighting a need for objective neurophysiological measures. Although P300 abnormalities have been well documented in adults with MDD, evidence in adolesce... read more 

Rumination is more important than other variables in the association between social media use and depression: A multi-method study.

Journal of affective disorders Jan 11, 2026
The relationship between social media use (SMU) and mental health, particularly depression, remains inconclusive. The present study recruited 925 college students from two universities in Chongqing, China, to further address this issue using multiple... read more 

A deep learning-based tool for rapid and automated detection of Cryptosporidium oocysts: A new approach for veterinary diagnostics and epizootiological surveys.

Experimental parasitology Jan 11, 2026
Cryptosporidiosis, caused by Cryptosporidium spp., is a significant zoonotic parasitic disease impacting neonatal calves, leading to severe diarrhea, dehydration, and substantial economic losses in the livestock industry. Rapid and accurate detection... 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 

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 

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 

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 

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 

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 

Shap-interpretable predictive modeling of microvascular invasion and early recurrence in hepatocellular carcinoma using MRI habitat imaging combined with clinical features.

European journal of radiology Jan 11, 2026
OBJECTIVE: To develop and validate an integrated model combining Gd-EOB-DTPA-enhanced MRI habitat imaging with clinical features for preoperative prediction of microvascular invasion (MVI) and early recurrence in hepatocellular carcinoma (HCC). METHO... read more 
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