Artificial Intelligence Medical Compendium

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

Showing 17,741 to 17,750 of 214,033 articles

Clinical Validation of Two New Planimetric Techniques for Measuring Ulcer Surface Area.

Journal of diabetes science and technology
BACKGROUND: As a standalone parameter, the wound surface area can be used to describe a wound in medical records; however, changes in the wound surface area over time can be used in chronic wounds to assess treatment efficacy and predict successful h... read more 

Integrated Machine Learning and Molecular Dynamics for Functional Nanoparticle Design: Synthesis, Characterization, Force-Field Development, and Property Prediction.

Langmuir : the ACS journal of surfaces and colloids
The integration of machine learning (ML) with molecular dynamics (MD) significantly enhances the design of nanoparticles (NPs) across four key areas: synthesis optimization, advanced characterization, ML-based force fields (MLFFs), and property predi... read more 

Artificial Intelligence-based Online Symptom Assessment Tools for Systemic Lupus Erythematosus (SLE) diagnosis: Patient Perspectives.

Arthritis care & research
OBJECTIVE: The objective of this article is to identify perceptions of SLE patients regarding artificial intelligence (AI)-based online symptom assessment tools, and the potential of these tools to address diagnostic barriers. METHODS: Adults from ou... read more 

Artificial Intelligence in Oral Cancer Diagnosis: A Bibliometric Mapping Study Based on Scopus Literature (2000-2025).

The Journal of craniofacial surgery
OBJECTIVE: To map global research trends in artificial intelligence (AI) applications for oral cancer diagnosis using bibliometric analysis. DESIGN: Publications retrieved from Scopus and PubMed (2000-2025) were analyzed using VOSviewer for keyword c... read more 

Empowering classification for multivariate functional data with simultaneous feature selection.

Statistical methods in medical research
The opportunity to utilize multivariate functional data types for conducting classification tasks is emerging with the growing availability of imaging data. Inspired by the extensive data provided by the Alzheimer's Disease Neuroimaging Initiative, w... read more 

Co-Evolution of the Activity and Thermostability of (R)-Transaminase AcTA by Data-Driven Exploration of Combinatorial Mutagenesis Space.

Journal of agricultural and food chemistry
Optically active (R)-amines are pivotal building blocks of a variety of agrochemicals and food-related bioactive compounds. To construct a biocatalytic route for the efficient synthesis of (R)-amines, a high-performance (R)-TA, AcTA from Aspergillus ... read more 

An examination of real-world disengagement patterns of automated driving systems in autonomous-mode: A deep-learning method.

Traffic injury prevention
OBJECTIVE: Widespread adoption of automated driving systems (ADS) depends fundamentally on their operational reliability. Frequent or unexpected disengagements pose a significant barrier by undermining user trust. Although human-automation interactio... read more 

Advancing equity in endometrial cancer: A narrative synthesis using a cluster-informed framework for resource-stratified implementation.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
Endometrial cancer incidence and mortality are rising globally, disproportionately affecting health systems facing diagnostic, therapeutic, and survivorship constraints. Rapid innovations-including the International Federation of Gynecology and Obste... read more 

T2-FLAIR digital subtraction radiomics versus neuroradiologist visual assessment for differentiating IDH-mutant astrocytomas from other non-enhancing low-grade gliomas: An externally validated machine learning study.

Neuroradiology
PURPOSE: Non-invasive differentiation of isocitrate dehydrogenase (IDH)-mutant, 1p/19q non-codeleted astrocytomas from other non-enhancing low-grade gliomas (LGGs) is crucial for treatment planning and prognostication, as these molecular subtypes hav... read more 

Automatic choroid plexus assessment in SLE: a deep learning-enabled study.

Neuroradiology
PURPOSE: This study developed a deep learning model for automated choroid plexus (ChP) segmentation and examined its relationship with systemic inflammation and processing speed and attention deficits (PSAD) in SLE patients without major neuropsychia... read more