BACKGROUND: Alzheimer disease and related dementias (ADRD) exhibit prominent heterogeneity. Identifying clinically meaningful ADRD subtypes is essential for tailoring treatments to specific patient phenotypes.
PURPOSE: This study aims to investigate the impact of tumor quadrant location on the 5-year early-stage breast cancer survivability prediction using explainable machine learning (ML) models. By integrating these predictive models with Shapley Additiv...
International journal of medical informatics
Mar 30, 2025
PURPOSE: To develop an AI-based diagnostic model for assessing cervical lymph nodes in head and neck malignant tumors using MRI, enabling non-invasive pre-surgical metastasis diagnosis.
Clinical biomechanics (Bristol, Avon)
Mar 30, 2025
BACKGROUND: Anterior lumbar interbody fusion is performed to fuse pathological spinal segments, generally, with a monobloc cage inserted by impact forces. Recently developed three-part modular cages attempt to reduce the impact forces, minimize the d...
Gait abnormality detection is a growing application in machine learning based health assessment due to its potential in domains from clinical health reviews to at home health monitoring. This latter application is of particular use for older adults, ...
BACKGROUND: Major bleeding is a severe complication in critically ill medical patients, resulting in significant morbidity, mortality, and healthcare costs. This study aims to assess the incidence and risk factors for major bleeding in hospitalised m...
OBJECTIVE: This study aimed to develop and validate a nomogram combining F-FDG PET radiomics and clinical factors to non-invasively predict bone marrow involvement (BMI) in patients with lymphoma.
Exploring the clinical significance of employing deep learning methodologies on ultrasound images for the development of an automated model to accurately identify pleomorphic adenomas and Warthin tumors in salivary glands. A retrospective study was c...
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