To develop and validate a machine learning (ML) model integrating multidimensional clinical, pathomic, and ultrasound radiomic parameters for precise identification of endometrial malignancy and precancerous lesions, with a focus on addressing the di...
BACKGROUND: Paediatric melanoma is a rare but important diagnosis. In the paediatric cohort, diagnostic challenges arise due to lesion variability and the inherent difficulties associated with paediatric assessment. Clinical decision-making is furthe...
Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery
Dec 15, 2025
OBJECTIVE: To explore, identify, and develop novel blood-based indicators using machine learning algorithms for accurate preoperative assessment and effective prediction of postoperative complication risks in patients with rheumatoid arthritis (RA) u...
BACKGROUND: Heart failure (HF) and diabetes mellitus (DM) frequently coexist, exacerbating disease progression and increasing hospital readmission risk. Accurate prediction of readmission in HF patients with DM remains a clinical challenge. This stud...
Anti-seizure medications (ASMs) are often prescribed using a trial-and-error approach with a similar sequence for many patients. Comparative effectiveness data beyond the first ASM prescription are limited. Artificial intelligence can automatically e...
AJNR. American journal of neuroradiology
Dec 4, 2025
BACKGROUND AND PURPOSE: Distinguishing GM from WM is essential for CT of the brain. The recently established photon-counting detector (PCD)-CT technology uses a novel detection technique that might allow more precise measurement of tissue attenuation...
AJNR. American journal of neuroradiology
Dec 4, 2025
BACKGROUND AND PURPOSE: Identifying amyloid-beta (Aβ)-positive patients is essential for Alzheimer disease clinical trials and disease-modifying treatments but currently requires PET or CSF sampling. Previous MRI-based deep learning models using only...
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