Artificial Intelligence Medical Compendium

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

Showing 66,171 to 66,180 of 232,257 articles

Identification of phosphodiesterase 10 A modulators for neurodegenerative and psychiatric disorders: Combination of physics-based virtual screening and machine learning approaches.

Computational biology and chemistry
Phosphodiesterase (PDE) is a crucial enzyme that regulates intracellular signal transduction by breaking down cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP) into inactive forms. Among the 11 PDE families, PDE10A has g... read more 

An Artificial Intelligence-Based Prognostic Model for Prediction of Functional Glaucoma Progression From Clinical and Structural Data.

American journal of ophthalmology
PURPOSE: Integration of various sources of information for prediction of disease progression is an unmet need in glaucoma diagnostics. We designed a deep learning-based prognostic model incorporating clinical and structural data for forecasting funct... read more 

Inaccurate information regarding cardiovascular disease prevention enabled by generative artificial intelligence.

American journal of preventive cardiology
Inaccurate information regarding cardiovascular disease (CVD) prevention is prevalent on the internet and may influence medical decisions. Artificial intelligence "bots" are present on the internet and may be used for medical questions. This physicia... read more 

Longitudinal changes in subcortical functional connectivity during Alzheimer's disease progression.

The journal of prevention of Alzheimer's disease
Human cognition and behavior rely on the integration of large-scale neural networks that connect the cerebral cortex and subcortical structures. Emerging evidence suggests that alterations in the functional connectivity (FC) between the cortical and ... read more 

Ccta-based AI for Diagnosing ≥ 50 % coronary Stenosis: A patient- and Vessel-Level meta-analysis.

European journal of radiology
BACKGROUND: To investigate the diagnostic performance of CCTA-based artificial intelligence (AI) in detecting ≥ 50 % coronary stenosis of coronary artery disease (CAD) at both the patient and vessel levels. METHODS: A systematic search of PubMed, Emb... read more 

CocoAdapter: Efficient end-to-end temporal action detection via self-constrained multi-cognitive adapters.

Neural networks : the official journal of the International Neural Network Society
End-to-end training in temporal action detection (TAD) has shown great potential for performance improvement by jointly optimizing the video encoder and action classification head. However, memory bottlenecks have limited the performance of end-to-en... read more 

Machine learning detecting aggression among mood disorder patients visited in psychiatric emergency departments.

Journal of affective disorders
BACKGROUND: Aggression, which is highly prevalent in patients with mood disorders, has been proven valuable in detecting the progression from hypomania to manic episode, enabling a timely diagnosis and treatment. OBJECTIVE: This study aims to develop... read more 

Plasma metabolomics identifies lipid mediators linking depression and cognitive decline in late-life depression.

Journal of affective disorders
BACKGROUND: Late-life depression (LLD) features recurrent episodes and frequently co-exists with cognitive impairment, which predicts worse outcomes and progression to dementia. Evidence indicates a bidirectional depression-cognition relationship, bu... read more 

Altered resting-state sensorimotor network in patients with obsessive-compulsive disorder: An EEG study.

Journal of affective disorders
BACKGROUND AND OBJECTIVE: Dysfunction in the cortical-striatal-thalamo-cortical circuit is considered a core pathological mechanism of obsessive-compulsive disorder (OCD) and may contribute to abnormalities in the sensorimotor network (SMN). Although... read more 

Metabolic-immune interactions in gastric cancer T cells: A single-cell atlas for prognostic biomarker identification.

Quantitative biology (Beijing, China)
Metabolic alterations and immune dysfunction within the gastric tumor microenvironment critically drive gastric cancer (GC) progression and therapeutic resistance. Although single-cell RNA sequencing (scRNA-seq) has unveiled cellular heterogeneity in... read more