Artificial Intelligence Medical Compendium

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

Showing 38,651 to 38,660 of 223,469 articles

Ten-Year Trends in Healthcare Use and Costs for People Living with Diabetes in France: Results from the Epicodiab Study Based on National Claims Data.

Diabetes therapy : research, treatment and education of diabetes and related disorders
INTRODUCTION: Diabetes remains a global public health concern, with increased prevalence and a significant economic burden. Yet, most studies do not differentiate between type 1 (T1D) and type 2 diabetes (T2D), despite distinct clinical trajectories ... read more 

Artificial intelligence in pediatric myopia - a narrative review.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
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Toward a multi-level, needs-based approach to cancer navigation: Considerations for service design.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
Evidence suggests that patient navigation can help address ongoing barriers to accessing timely, appropriate, and quality cancer care. It also supports people affected by cancer to navigate through complex health care systems. Cancer patient navigati... read more 

U-Net-based transfer learning for automated tumour segmentation enabling fully automated [18F]F-DOPA PET analysis in paediatric gliomas.

Brain informatics
BACKGROUND: PET imaging with [18F]F-DOPA shows great promise for assessing paediatric gliomas. Manual tumour delineation and parameter extraction are time-consuming and prone to inter-operator variability. METHODS: We evaluated whether a deep learnin... read more 

Integrating Mechanistic Modeling and Machine Learning to Study CD4+/CD8+ CAR-T Cell Dynamics with Tumor Antigen Regulation.

Bulletin of mathematical biology
Chimeric antigen receptor (CAR) T cell therapy has shown remarkable success in hematological malignancies, yet patient responses remain highly variable and the roles of CD4+ and CD8+ subsets are not fully understood. We present an extended mathematic... read more 

An interpretable machine learning model combining MRI-DKI habitat radiomic features and clinical biomarkers for noninvasive prediction of lymphatic metastasis in rectal cancer: a prospective study.

Insights into imaging
OBJECTIVE: Tumor heterogeneity exerts a significant influence on lymphovascular invasion (LVI) and lymph node metastasis (LNM) in rectal cancer (RC), thereby affecting patient treatment outcomes and prognosis. This study aims to develop a combined mo... read more