Convolutional neural networks for radiologic images: a radiologist's guide
S Soffer, A Ben-Cohen, O Shimon, MM Amitai… - Radiology, 2019 - pubs.rsna.org
Deep learning has rapidly advanced in various fields within the past few years and has
recently gained particular attention in the radiology community. This article provides an …
recently gained particular attention in the radiology community. This article provides an …
Deep learning for wireless capsule endoscopy: a systematic review and meta-analysis
Background and Aims Deep learning is an innovative algorithm based on neural networks.
Wireless capsule endoscopy (WCE) is considered the criterion standard for detecting small …
Wireless capsule endoscopy (WCE) is considered the criterion standard for detecting small …
Application of deep learning for fast detection of COVID-19 in X-Rays using nCOVnet
Presently, COVID-19 has posed a serious threat to researchers, scientists, health
professionals, and administrations around the globe from its detection to its treatment. The …
professionals, and administrations around the globe from its detection to its treatment. The …
Creating artificial images for radiology applications using generative adversarial networks (GANs)–a systematic review
Rationale and Objectives Generative adversarial networks (GANs) are deep learning
models aimed at generating fake realistic looking images. These novel models made a great …
models aimed at generating fake realistic looking images. These novel models made a great …
Deep learning for natural language processing in radiology—fundamentals and a systematic review
Purpose Natural language processing (NLP) enables conversion of free text into structured
data. Recent innovations in deep learning technology provide improved NLP performance …
data. Recent innovations in deep learning technology provide improved NLP performance …
Deep learning algorithms for automated detection of Crohn's disease ulcers by video capsule endoscopy
Background and Aims The aim of our study was to develop and evaluate a deep learning
algorithm for the automated detection of small-bowel ulcers in Crohn's disease (CD) on …
algorithm for the automated detection of small-bowel ulcers in Crohn's disease (CD) on …
[HTML][HTML] Medical image processing and COVID-19: a literature review and bibliometric analysis
COVID-19 crisis has placed medical systems over the world under unprecedented and
growing pressure. Medical imaging processing can help in the diagnosis, treatment, and …
growing pressure. Medical imaging processing can help in the diagnosis, treatment, and …
Reinventing polysomnography in the age of precision medicine
DC Lim, DR Mazzotti, K Sutherland, JW Mindel… - Sleep medicine …, 2020 - Elsevier
For almost 50 years, sleep laboratories around the world have been collecting massive
amounts of polysomnographic (PSG) physiological data to diagnose sleep disorders, the …
amounts of polysomnographic (PSG) physiological data to diagnose sleep disorders, the …
Artificial intelligence in breast imaging: potentials and limitations
EB Mendelson - American Journal of Roentgenology, 2019 - Am Roentgen Ray Soc
OBJECTIVE. The purpose of this article is to discuss potential applications of artificial
intelligence (AI) in breast imaging and limitations that may slow or prevent its adoption …
intelligence (AI) in breast imaging and limitations that may slow or prevent its adoption …
An integrated framework of skin lesion detection and recognition through saliency method and optimal deep neural network features selection
Malignant melanoma, not belongs to a common type of skin cancers but most serious
because of its growth—affecting large number of people worldwide. Recent studies …
because of its growth—affecting large number of people worldwide. Recent studies …