[HTML][HTML] A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta …

X Liu, L Faes, AU Kale, SK Wagner, DJ Fu… - The lancet digital …, 2019 - thelancet.com
Background Deep learning offers considerable promise for medical diagnostics. We aimed
to evaluate the diagnostic accuracy of deep learning algorithms versus health-care …

Artificial convolutional neural network in object detection and semantic segmentation for medical imaging analysis

R Yang, Y Yu - Frontiers in oncology, 2021 - frontiersin.org
In the era of digital medicine, a vast number of medical images are produced every day.
There is a great demand for intelligent equipment for adjuvant diagnosis to assist medical …

Convolutional neural networks for medical image analysis: state-of-the-art, comparisons, improvement and perspectives

H Yu, LT Yang, Q Zhang, D Armstrong, MJ Deen - Neurocomputing, 2021 - Elsevier
Convolutional neural networks, are one of the most representative deep learning models.
CNNs were extensively used in many aspects of medical image analysis, allowing for great …

Deep learning-based model for detecting 2019 novel coronavirus pneumonia on high-resolution computed tomography

J Chen, L Wu, J Zhang, L Zhang, D Gong, Y Zhao… - Scientific reports, 2020 - nature.com
Computed tomography (CT) is the preferred imaging method for diagnosing 2019 novel
coronavirus (COVID19) pneumonia. We aimed to construct a system based on deep …

Application of artificial intelligence to gastroenterology and hepatology

C Le Berre, WJ Sandborn, S Aridhi, MD Devignes… - Gastroenterology, 2020 - Elsevier
Since 2010, substantial progress has been made in artificial intelligence (AI) and its
application to medicine. AI is explored in gastroenterology for endoscopic analysis of …

Expected value of artificial intelligence in gastrointestinal endoscopy: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement

H Messmann, R Bisschops, G Antonelli, D Libânio… - …, 2022 - thieme-connect.com
This ESGE Position Statement defines the expected value of artificial intelligence (AI) for the
diagnosis and management of gastrointestinal neoplasia within the framework of the …

[HTML][HTML] Artificial intelligence in gastroenterology: A state-of-the-art review

PT Kröner, MML Engels, BS Glicksberg… - World journal of …, 2021 - ncbi.nlm.nih.gov
The development of artificial intelligence (AI) has increased dramatically in the last 20 years,
with clinical applications progressively being explored for most of the medical specialties …

[HTML][HTML] Evaluation of the effects of an artificial intelligence system on endoscopy quality and preliminary testing of its performance in detecting early gastric cancer: a …

L Wu, X He, M Liu, H **e, P An, J Zhang, H Zhang… - …, 2021 - thieme-connect.com
Background Esophagogastroduodenoscopy (EGD) is a prerequisite for detecting upper
gastrointestinal lesions especially early gastric cancer (EGC). An artificial intelligence …

Prevalence and diagnosis of neurological disorders using different deep learning techniques: a meta-analysis

R Gautam, M Sharma - Journal of medical systems, 2020 - Springer
This paper dispenses an exhaustive review on deep learning techniques used in the
prognosis of eight different neuropsychiatric and neurological disorders such as stroke …

Detecting early gastric cancer: Comparison between the diagnostic ability of convolutional neural networks and endoscopists

Y Ikenoyama, T Hirasawa, M Ishioka… - Digestive …, 2021 - Wiley Online Library
Objectives Detecting early gastric cancer is difficult, and it may even be overlooked by
experienced endoscopists. Recently, artificial intelligence based on deep learning through …