The first step in the automatic evaluation of the cardiac prosthetic valve is the recognition of such valves in echocardiographic images. This research surveyed whether a deep convolutional neural network (DCNN) could improve the recognition of prost...
Understanding a patient's medical history, such as how long symptoms last or when a procedure was performed, is vital to diagnosing problems and providing good care. Frequently, important information regarding a patient's medical timeline is buried i...
AJR. American journal of roentgenology
Apr 14, 2021
Previous advances over filtered back projection (FBP) have incorporated model-based iterative reconstruction. The purpose of this study was to characterize the latest advance in image reconstruction, that is, deep learning. The focus was on applying...
OBJECTIVES: To evaluate a deep learning model for predicting gestational age from fetal brain MRI acquired after the first trimester in comparison to biparietal diameter (BPD).
OBJECTIVES: The aim of this study was to develop pre-procedural intravascular ultrasound (IVUS)-based models for predicting the occurrence of stent underexpansion.
In recent years, various studies have begun to use deep learning models to conduct research in the field of human activity recognition (HAR). However, there has been a severe lag in the absolute development of such models since training deep learning...
PURPOSE OF REVIEW: Recently numerous researchers have shown remarkable progress using convolutional neural network-based artificial intelligence (AI) for endoscopy. In this manuscript we aim to summarize recent AI impact on endoscopy.
The differentiation between major histological types of lung cancer, such as adenocarcinoma (ADC), squamous cell carcinoma (SCC), and small-cell lung cancer (SCLC) is of crucial importance for determining optimum cancer treatment. Hematoxylin and Eos...
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