BACKGROUND: The burden of asymptomatic left ventricular dysfunction (LVD) is greater than that of heart failure; however, a cost-effective tool for asymptomatic LVD screening has not been well validated. We aimed to prospectively validate an artifici...
BACKGROUND: The gold standard to diagnose fatty liver is pathology. Recently, image-based artificial intelligence (AI) has been found to have high diagnostic performance. We systematically reviewed studies of image-based AI in the diagnosis of fatty ...
BACKGROUND: Deep learning models have had a lot of success in various fields. However, on structured data they have struggled. Here we apply four state-of-the-art supervised deep learning models using the attention mechanism and compare against logis...
Journal of the Formosan Medical Association = Taiwan yi zhi
Dec 2, 2023
BACKGROUND: Alzheimer's disease (AD) is complicated by multiple environmental and polygenetic factors. The accuracy of artificial neural networks (ANNs) incorporating the common factors for identifying AD has not been evaluated.
Retinitis pigmentosa (RP) is often undetected in its early stages. Artificial intelligence (AI) has emerged as a promising tool in medical diagnostics. Therefore, we conducted a systematic review and meta-analysis to evaluate the diagnostic accuracy ...
Computer methods and programs in biomedicine
Nov 30, 2023
BACKGROUND AND OBJECTIVE: Protein-protein interaction (PPI) is a vital process in all living cells, controlling essential cell functions such as cell cycle regulation, signal transduction, and metabolic processes with broad applications that include ...
INTRODUCTION: In this study, we aimed to compare the performance of a convolutional neural network (CNN)-based deep learning model that was trained on a dataset of normal and abnormal paediatric elbow radiographs with that of paediatric emergency dep...
Journal of magnetic resonance imaging : JMRI
Nov 29, 2023
BACKGROUND: Glioma grading transformed in World Health Organization (WHO) 2021 CNS tumor classification, integrating molecular markers. However, the impact of this change on radiomics-based machine learning (ML) classifiers remains unexplored.
Inattention of economic policymakers to default risk and making inappropriate decisions related to this risk in the banking system and financial institutions can have many economic, political and social consequences. In this research, it has been tri...
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