Artificial Intelligence Medical Compendium

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

Showing 37,071 to 37,080 of 223,469 articles

Artificial intelligence for educating family caregivers of people with dementia: A mixed methods systematic review.

Geriatric nursing (New York, N.Y.)
Dementia is a growing global health challenge, with the majority of individuals living with dementia receiving care from family members. However, many family caregivers lack sufficient knowledge, skills, and emotional support. Emerging artificial int... read more 

A scalable EEG-based spatial neglect detection system in augmented reality for stroke patients.

Journal of neuroscience methods
BACKGROUND: Spatial neglect is a common visuospatial attention disorder following a stroke. To overcome weaknesses associated with classic pen-and-paper tests used in some clinical settings, we developed AREEN: an AR-guided EEG-based Neglect detectio... read more 

From prediction to precision: how immunopeptidomics advances neoantigen discovery.

Trends in cancer
T cell recognition of peptides presented by class I and II human leukocyte antigen (HLA) molecules is fundamental to cancer immunity and personalized immunotherapy. Neoantigens, peptides containing somatic mutations, are attractive therapeutic target... read more 

Deep learning model for pathological invasiveness prediction using smartphone-based surgical resection images in clinical stage IA lung adenocarcinoma (SuRImage): a prospective, multicentric, diagnostic study.

The Lancet. Digital health
BACKGROUND: In clinical stage IA lung adenocarcinoma (LUAD), rapid and accurate intraoperative diagnosis is crucial to decide whether to perform segmentectomy and lobectomy. Frozen section analysis is time consuming and not always reliable for LUAD d... read more 

ProteinMCP: An agentic AI framework for autonomous protein engineering.

Protein science : a publication of the Protein Society
Computational protein design is often constrained by slow, complex, inaccessible, and highly sophisticated and expert-dependent workflows that hinder its transferrability and generalization power for broader applications. We present ProteinMCP, an ag... read more 

Multicentre Evaluation of an AI-Assisted Urine Test for Clinically Significant Prostate Cancer in Men Undergoing Initial Biopsy.

Journal of extracellular vesicles
The Extracellular Vesicles Gene-based Prostate Score (EGPS), powered by DeepSeek, is an artificial intelligence (AI) diagnostic tool that enhances the detection of clinically significant prostate cancer (csPCa) using urinary EV-derived gene expressio... read more 

Integration of Machine Learning With PBPK and QSAR Modeling Approaches to Facilitate Drug Discovery and Development.

CPT: pharmacometrics & systems pharmacology
This review examines the application of machine learning (ML) in physiologically based pharmacokinetic (PBPK) modeling through improved prediction of input parameters, particularly via quantitative structure-activity relationship (QSAR) models, for a... read more 

[Application of artificial intelligence to pharmacological and interventional treatment].

Giornale italiano di cardiologia (2006)
As in many other fields, artificial intelligence (AI) is transforming daily activities in cardiology. In pharmacological therapy, algorithms have been developed to prevent adverse reactions, improve therapeutic adherence, and optimize dosage. In the ... read more 

Artificial intelligence in emergency medicine: from expectation to implementation.

Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias
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Assessment of the risk of bacteremia in patients with hematologic malignancies in the emergency department: A comparative study between logistic regression and machine learning algorithms.

Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias
OBJECTIVE: To stratify the risk of bacteremia at the time of emergency department (ED) admission in patients with hematologic malignancies. To this end, we compared the performance of unsupervised and supervised machine learning algorithms with the c... read more