Artificial Intelligence Medical Compendium

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

Showing 65,621 to 65,630 of 232,257 articles

Latest research

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

Neural networks : the official journal of the International Neural Network Society
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 

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

Experimental gerontology
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 

Neural signatures of major depressive disorder with comorbid insomnia: Low gamma PoCG.R-INS.L connectivity as a potential biomarker.

Journal of affective disorders
BACKGROUND: Insomnia is a common and distressing symptom in major depressive disorder (MDD). However, research focusing on the neurobiological mechanisms of MDD with comorbid insomnia remains limited, and objective biomarkers are still lacking. There... read more 

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

Journal of affective disorders
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
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
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
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
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
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
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