Computational intelligence and neuroscience
Apr 26, 2022
Food is the paramount necessity of the people. With the progress of society and the improvement of social welfare system, the living standards of people all over the world are constantly improving. The development of medical industry improves people'...
Researchers and practitioners often use single-case designs (SCDs), or n-of-1 trials, to develop and validate novel treatments. Standards and guidelines have been published to provide guidance as to how to implement SCDs, but many of their recommenda...
PURPOSE: The aim of the study is to improve the accuracy of age related macular degeneration (AMD) disease in its earlier phases with proposed Capsule Network (CapsNet) architecture trained on speckle noise reduced spectral domain optical coherence t...
Journal of the American College of Radiology : JACR
Apr 25, 2022
Federated learning is a machine learning method that allows decentralized training of deep neural networks among multiple clients while preserving the privacy of each client's data. Federated learning is instrumental in medical imaging because of the...
Journal of laparoendoscopic & advanced surgical techniques. Part A
Apr 25, 2022
To determine the stone-free rates (SFR) with robot-assisted mini-endoscopic combined intrarenal surgery (mini-ECIRS) and evaluate the impact of intraoperative assessment of stone-free status compared to postoperative non-contrast computed tomography...
After our coauthors described the first remote-access parathyroidectomy (RAP) series in 2000, several other approaches were developed. No systematic review has been performed to classify and evaluate RAP techniques. We performed a literature search u...
The deployment of machine learning for tasks relevant to complementing standard of care and advancing tools for precision health has gained much attention in the clinical community, thus meriting further investigations into its broader use. In an int...
Myocardial infarction (MI) accounts for a high number of deaths globally. In acute MI, accurate electrocardiography (ECG) is important for timely diagnosis and intervention in the emergency setting. Machine learning is increasingly being explored for...
Although natural language processing (NLP) can rapidly extract disease labels from radiology reports to create datasets for deep learning models, this may be less accurate than having radiologists manually review the images. In this study, we compare...
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