… development for automated diagnosis from TTE. For this reason, despite the clinical
importance of TTE and the rise of deep learning for medical imaging 4 , deep learning techniques …

… This study proposed an automated diagnostic tool called “DIAROP” based on DL techniques.
It can be considered as a reliable diagnostic tool that can classify ROP with high accuracy …

… diagnosing patients with Alzheimer’s disease (AD) and mild cognitive impairment (MCI). The
advanced deep learning … the diagnostic accuracy of AD. Three-dimensional convolutional …

… Third, although a promising framework in this paper was provided for an automated detection
of retinal diseases, the correct classification of a specific retinal disorders (such as diabetic …

… In view of these limitations, in this paper, we proposed DeepFD, a learning-based fault
diagnosis and localization framework which maps the fault localization task to a learning problem. …

… of research of integrating complex ensemble deep learning models with Edge Computing
… but also is able to use deep learning based frameworks to provide highly accurate results. …

… presented a deep learning-based framework for automated lung cancer … a deep learning-based
framework for automated lung cancer detection was proposed. The proposed framework …

… machine learning based framework that analyzes pupil-size dynamics as an objective biomarker
for the automated … As such, we sought to develop a machine learning-based framework …

… fully-automated and fast robotic perception framework is proposed to diagnosis the bean …
Firstly, the U-Net based ResNet model is applied to accurately and automatically detect the …

… deep learning-based framework for histopathology tissue analysis to address these
challenges. Our framework is, in … An automated end-to-end deep learning-based framework for …