BACKGROUND: The objective of this study was to develop and validate a radiomics-based machine learning (ML) model to differentiate between renal medullary carcinoma (RMC) and clear cell renal carcinoma (ccRCC).
Investigative ophthalmology & visual science
Feb 3, 2025
PURPOSE: To compare the prediction accuracy of brachial-ankle pulse wave velocity (baPWV) from color fundus photographs (CFPs) using different deep learning models.
OBJECTIVE: To explore the feasibility of incorporating simple bedside indicators into death predictive model for elderly critically ill patients based on interpretability machine learning algorithms, providing a new scheme for clinical disease assess...
We developed a machine learning model for predicting prostate cancer (PCa) grades using radiomic features of magnetic resonance imaging. 112 patients diagnosed with PCa based on prostate biopsy between January 2014 and December 2021 were evaluated. L...
Background Incomplete clinical histories are a well-known problem in radiology. Previous dedicated quality improvement efforts focusing on reproducible assessments of the completeness of free-text clinical histories have relied on tedious manual anal...
Journal of cachexia, sarcopenia and muscle
Feb 1, 2025
BACKGROUND: Hospital falls are the most prevalent and fatal event in healthcare, posing significant risks to patient health outcomes and institutional care quality. Real-time location system (RTLS) enables continuous tracking of patient location, pro...
Journal of cellular and molecular medicine
Feb 1, 2025
Endometrial cancer (EC) incidence and the associated tumour burden have increased globally. To build a molecular expression prognostic model based on the tumour microenvironment to guide personalised treatment using a machine learning approach. Two d...
Background Deep learning (DL) methods enable faster shoulder MRI than conventional methods, but arthroscopy-validated evidence of good diagnostic performance is scarce. Purpose To validate the clinical efficacy of 7-minute threefold parallel imaging ...
The Journal of international medical research
Feb 1, 2025
OBJECTIVE: To study the classification performance of a pre-trained convolutional neural network (CNN) with transfer learning by artificial joint ultrasonography images in rheumatoid arthritis (RA).
Background Combined mammography and MRI screening is not universally accessible for women with intermediate breast cancer risk due to limited MRI resources. Selecting women for MRI by assessing their mammogram may enable more resource-effective scree...
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