Leprosy is a dermatoneurological disease and can cause irreversible nerve damage. In addition to being able to mimic different rheumatological, neurological and dermatological diseases, leprosy is underdiagnosed because several professionals present ...
OBJECTIVE: This study developed and validated a stacked ensemble machine learning model to predict the risk of acute kidney injury in patients with acute pancreatitis complicated by sepsis.
More than 90% of deaths due to breast cancer (BC) are due to metastasis-related complications, with invasive ductal carcinoma (IDC) of the breast being the most common pathologic type of breast cancer and highly susceptible to metastasis to distant o...
BACKGROUND: To compare the influence of rectal susceptibility artifacts on the subjective evaluation and deep learning (DL) in prostate cancer (PCa) diagnosis.
Early diagnosis of Kawasaki disease (KD) allows timely treatment to be initiated, thereby preventing coronary artery aneurysms in children. However, it is challenging due to the subjective nature of the diagnostic criteria. This study aims to develop...
PURPOSE: Neonatal activity is an important physiological parameter in the neonatal intensive care unit (NICU). The degree of neonatal activity is associated with under and over-sedation and may also indicate the onset of disease. Activity may also ca...
PURPOSE: This study aimed to assess the diagnostic accuracy of combining MRI hand-crafted (HC) radiomics features with deep transfer learning (DTL) in identifying sinonasal squamous cell carcinoma (SCC), adenoid cystic carcinoma (ACC), and non-Hodgki...
BACKGROUND: An ideal lung allocation system should reduce waiting list deaths, improve transplant survival, and ensure equitable organ allocation. This study aimed to develop a novel lung allocation score (LAS) system, the MaxBenefit LAS, to maximize...
International journal of medical informatics
Feb 22, 2025
BACKGROUND: The 30-day hospital readmission rate is a key indicator of healthcare quality and system efficiency. This study aimed to develop machine-learning (ML) models to predict unplanned 30-day readmissions in older patients with ischemic stroke ...