Artificial Intelligence Medical Compendium
Explore the latest research on artificial intelligence and machine learning in medicine.
Showing 431 to 440 of 158,332 articles
MRI-based interpretable clinicoradiological and radiomics machine learning model for preoperative prediction of pituitary macroadenomas consistency: a dual-center study.
Neuroradiology
Jul 9, 2025
PURPOSE: To establish an interpretable and non-invasive machine learning (ML) model using clinicoradiological predictors and magnetic resonance imaging (MRI) radiomics features to predict the consistency of pituitary macroadenomas (PMAs) preoperative...
Medical needles in the hands of AI: Advancing toward autonomous robotic navigation.
Science robotics
Jul 9, 2025
Safely and accurately navigating needles percutaneously or endoscopically to sites deep within the body is essential for many medical procedures, from biopsies to localized drug deliveries to tumor ablations. The advent of image guidance decades ago ...
Artificial Intelligence in Higher Education: Legal Accountability and Best Practices for Upholding Student Privacy and Nondiscrimination Rights.
The journal of physician assistant education : the official journal of the Physician Assistant Education Association
Jul 9, 2025
Artificial intelligence (AI) is increasingly being used across a broad spectrum of careers and institutions, with its adoption in the setting of higher education expected to exponentially increase in the coming years. As its relevance and use increas...
The association of life's essential 8 with prevalence of chronic respiratory diseases in adults: insights from NHANES 2007-2018.
BMC pulmonary medicine
Jul 9, 2025
OBJECTIVE: Chronic respiratory diseases (CRDs) and cardiovascular diseases (CVD) share common risk factors and frequently co-occur, leading to poorer outcomes. Life's Essential 8 (LE8), a novel metric for cardiovascular health, may provide insights i...
Metastability and Ostwald step rule in the crystallisation of diamond and graphite from molten carbon.
Nature communications
Jul 9, 2025
Experimental challenges in determining the phase diagram of carbon at temperatures and pressures near the graphite-diamond-liquid triple point are often related to the persistence of metastable crystalline or glassy phases, superheated crystals, or s...
Integrated Nanopore and short-read RNA sequencing identifies dysregulation of METTL3- m6A modifications in endocrine therapy- sensitive and resistant breast cancer cells.
Functional & integrative genomics
Jul 9, 2025
The role of epitranscriptomic changes in the development of acquired endocrine therapy (ET)- resistance in estrogen receptor α (ER) expressing breast cancer (BC) is unknown. We tested the hypothesis that inhibition of METTL3, the methyltransferase re...
Machine learning models for predicting multimorbidity trajectories in middle-aged and elderly adults.
Scientific reports
Jul 9, 2025
Multimorbidity has emerged as a significant public health issue in the context of global population aging. Predicting and managing the progression of multimorbidity in the elderly population is crucial. This study aims to develop predictive models fo...
Machine learning for synchronous bone metastasis risk prediction in high grade lung neuroendocrine carcinoma.
Scientific reports
Jul 9, 2025
Bone metastasis (BM) is common in high-grade lung neuroendocrine tumors (NETs). This study aimed to use multiple machine learning algorithms to exploring the significant factors associated with synchronous BM in these patients. Patients diagnosed wit...
Enhanced detection of Mpox using federated learning with hybrid ResNet-ViT and adaptive attention mechanisms.
Scientific reports
Jul 9, 2025
Monkeypox (Mpox), caused by the monkeypox virus, has become a global concern due to its rising cases and resemblance to other rash-causing diseases like chickenpox and measles. Traditional diagnostic methods, including visual examination and PCR test...
Attribution-based interpretable classification neural network with global and local perspectives.
Scientific reports
Jul 9, 2025
Neural networks are challenging to apply in domains requiring high reliability due to their black-box nature, and researchers are increasingly focusing on interpreting neural networks. While pursuing neural network performance, most methods often sac...
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