Artificial Intelligence Medical Compendium
Explore the latest research on artificial intelligence and machine learning in medicine.
Showing 64,921 to 64,930 of 231,605 articles
Artificial Intelligence and Trichoscopy: Can AI Distinguish Between Alopecia Areata and Lichen Planopilaris?
International journal of dermatology
Jan 12, 2026
Predicting Chronicity in Children and Adolescents With Newly Diagnosed Immune Thrombocytopenia at the Timepoint of Diagnosis Using Machine Learning-Based Approaches.
Pediatric blood & cancer
Jan 12, 2026
OBJECTIVES: To identify predictors of chronic ITP (cITP) and to develop a model based on several machine learning (ML) methods to estimate the individual risk of chronicity at the timepoint of diagnosis. METHODS: We analyzed a longitudinal cohort of ... read more
Prediction of the Preclinical Stage of Coal Workers' Pneumoconiosis on Nonimaging Data Integrating Prior Knowledge and Machine Learning.
Journal of occupational and environmental medicine
Jan 12, 2026
OBJECTIVE: This study aims to establish machine learning models using nonimaging data from health examinations of coal workers, which can screen the preclinical stage of coal workers' pneumoconiosis (CWP). METHODS: Nonimaging data from two centers, t... read more
A nomogram model for challenging cases: differentiating fat-poor angiomyolipoma from clear cell renal cell carcinoma in uncertain or misdiagnosed tumors.
Abdominal radiology (New York)
Jan 12, 2026
PURPOSE: To develop and validate a nomogram model that can accurately differentiate fat-poor angiomyolipoma (fp-AML) from clear cell renal cell carcinoma (ccRCC) in clinically challenging scenarios where conventional imaging diagnosis is uncertain or... read more
Automated detection of gallbladder stones using a deep learning algorithm on computed tomography scans.
Abdominal radiology (New York)
Jan 12, 2026
PURPOSE: To develop and evaluate the diagnostic accuracy of a deep learning algorithm for automated gallstone detection on CT. METHODS: This retrospective single-center study included randomly selected CT scans from January 2018 to June 2019: 493 gal... read more
Multi-center evaluation of radiomics and deep learning to stratify malignancy risk of IPMNs.
Abdominal radiology (New York)
Jan 12, 2026
PURPOSE: Distinguishing high-risk intraductal papillary mucinous neoplasms (IPMNs) from low-risk lesions remains a clinical challenge, often resulting in unnecessary procedures due to limited specificity of current methods. While radiomics and deep l... read more
AI for screening in healthcare: promise and challenges.
Abdominal radiology (New York)
Jan 12, 2026
Artificial intelligence (AI) is reshaping population screening, yet the translation from laboratory performance to population benefit remains limited. This narrative review describes current uses of AI across major screening pathways. Prospective tri... read more
Deep learning in enhanced CT imaging: predicting invasion depth of rectal adenocarcinoma.
Abdominal radiology (New York)
Jan 12, 2026
PURPOSE: This study aims to develop and evaluate a deep learning model, RectoDepthAI, that leverages enhanced CT images to accurately assess the tumor invasion depth in rectal adenocarcinoma, distinguishing between early-stage (submucosal or muscular... read more
Multimodal ultrasound assessment of ovarian reserve.
Abdominal radiology (New York)
Jan 12, 2026
Ovarian reserve represents the quantity and quality of a woman's remaining oocytes and serves as a key indicator of reproductive potential. Accurate and non-invasive evaluation of ovarian reserve is essential for guiding fertility management, predict... read more
Decoupling Bubble Nucleation from Catalysis to Boost CuxO/NiO Electrocatalytic Water Splitting.
Nano letters
Jan 12, 2026
Efficient water splitting requires low overpotentials and mitigated bubble-induced mass transfer resistance at high current densities. However, the conflict between catalysis and bubble management intensifies at these currents, blocking mass transfer... read more
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