The purpose of this study is to examine if aqueous autotaxin (ATX) and TGF-β levels could be used for differentiating glaucoma subtypes. This prospective observational study was performed using aqueous humor samples obtained from 281 consecutive pati...
BACKGROUND: Radical cystectomy with pelvic lymph node dissection (PLND) and urinary diversion in patients with bladder cancer is known for its high risk of complications. Although open radical cystectomy (ORC) is regarded as the standard treatment, r...
BACKGROUND: Recently, robot-assisted thoracic surgery (RATS) is increasingly applied to lung or mediastinal tumor surgery. However, appropriate methods of postoperative analgesia for RATS have not been studied.
IEEE journal of biomedical and health informatics
Jan 5, 2021
The prospective identification of children likely to develop schizophrenia is a vital tool to support early interventions that can mitigate the risk of progression to clinical psychosis. Electroencephalographic (EEG) patterns from brain activity and ...
BACKGROUND/AIMS: During the natural course of Chronic Hepatitis B (CHB) infection, differentiation between inactive carrier (IC) and HBeAg negative CHB is a subject of ongoing debate. We studied the role of hepatitis B surface antigen (HBsAg) level a...
PURPOSE: The role of tumor-infiltrating lymphocytes (TILs) in predicting lymph node metastasis (LNM) in patients with T1 colorectal cancer (CRC) remains unclear. Furthermore, clinical utility of a machine learning-based approach has not been widely s...
Best practice & research. Clinical gastroenterology
Dec 29, 2020
Artificial intelligence (AI) is of keen interest for global health development as potential support for current human shortcomings. Gastrointestinal (GI) endoscopy is an excellent substrate for AI, since it holds the genuine potential to improve qual...
OBJECTIVES/HYPOTHESIS: To create a new strategy for monitoring pediatric otitis media (OM), we developed a brief, reliable, and objective method for automated classification using convolutional neural networks (CNNs) with images from otoscope.
OBJECTIVES: Based on the current clinical routine, we aimed to develop a novel deep learning model to distinguish coronavirus disease 2019 (COVID-19) pneumonia from other types of pneumonia and validate it with a real-world dataset (RWD).
Journal of magnetic resonance imaging : JMRI
Dec 26, 2020
Current contrast-enhanced magnetic resonance angiography (MRA) and non-contrast-enhanced balanced steady-state free precession (bSSFP) MRA cause susceptibility artifacts from metallic devices in assessing endovascular visceral-artery interventions. T...
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