Artificial Intelligence Medical Compendium

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

Showing 32,591 to 32,600 of 221,076 articles

Wooden-Tip Electrospray Ionization Mass Spectrometry Combined With Machine Learning for Differentiating Thyroid Tumours.

Analytical science advances
Direct mass spectrometry (MS) analysis of human tissues at the molecular level has great potential for clinical diagnosis and biomarker discovery. However, conventional MS-based analytical methods often require complicated and time-consuming sample p... read more 

The multi-target cardiac protection mechanism of butylphthalide and AI-driven precision medicine: From molecular basis to clinical translation.

Ageing research reviews
Butylphthalide (NBP) is a lipophilic small-molecule drug characterized by its multi-target and multi-pathway regulatory properties. Initially employed in the treatment of ischemic stroke, recent studies have highlighted its significant protective eff... read more 

Evaluating carbon efficiency across the lithium-ion battery industry using a SMOTE-augmented Super-SBM approach.

Environmental research
The lithium-ion battery (LIB) industry, a cornerstone of energy storage technology, is critical in the global transition towards low-carbon energy systems. However, its carbon emission performance remains poorly understood. This study developed a hyb... read more 

Regional economy, physical environment and self-rated health among older adults in China: Evidence from XGBoost and SHAP.

Environmental research
Although the effects of the regional economy and physical environment on self-rated health among older adults in China have been widely recognized, their confounding relationships and non-linear impacts remain insufficiently understood. This study dr... read more 

Batch Size Effects on Mid-2025 State-of-the-Art Large Language Model Performance in Automated Title and Abstract Screening.

Cochrane evidence synthesis and methods
BACKGROUND: Manual abstract screening is a primary bottleneck in evidence synthesis. Emerging evidence suggests that large language models (LLMs) can automate this task, but their performance when processing multiple references simultaneously in "bat... read more 

Multidimensional cortical morphological alterations in COPD using explainable machine learning.

iScience
Cognitive dysfunction is a common extrapulmonary manifestation of chronic obstructive pulmonary disease (COPD). Here, we applied an XGBoost-SHAP machine learning framework to identify cortical morphological features related to cognitive performance i... read more 

MRDGNN: A multi-relational reasoning framework for predicting drug indications via relational digraphs.

Computational biology and chemistry
Predicting drug indications is a fundamental task in biomedical research and drug repurposing. In addition to known therapeutic associations, clinically relevant but opposite signals, such as contraindications, may provide complementary evidence for ... read more 

Restoring auditory discrimination in noise: mismatch negativity evidence for a deep neural network-based denoising system in hearing aids.

Hearing research
BACKGROUND: Understanding speech in noise is a primary challenge for individuals with sensorineural hearing loss (SNHL). While deep neural network (DNN)-based noise reduction in hearing aids shows behavioral promise, objective neurophysiological evid... read more 

Tear fluid multi-omics and biosensor integration for diagnosis and personalized therapeutics in dry eye disease.

Experimental eye research
Dry Eye Disease (DED) is increasingly recognized as a complicated, multi-factorial disease involving oxidative damage, metabolic dysregulation and immune dysregulation on the ocular surface. New data emerging from proteomics, lipidomics, metabolomics... read more 

An Introduction to Machine Learning for the Pediatric Hospitalist.

Hospital pediatrics
Machine learning models are increasingly used in clinical research to predict patient outcomes, yet many clinicians lack the training to critically appraise these studies. This article provides a conceptual introduction to machine learning for the pe... read more