U-net and its variants for medical image segmentation: A review of theory and applications

N Siddique, S Paheding, CP Elkin… - IEEE access, 2021 - ieeexplore.ieee.org
U-net is an image segmentation technique developed primarily for image segmentation
tasks. These traits provide U-net with a high utility within the medical imaging community …

Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans

M Roberts, D Driggs, M Thorpe, J Gilbey… - Nature Machine …, 2021 - nature.com
Abstract Machine learning methods offer great promise for fast and accurate detection and
prognostication of coronavirus disease 2019 (COVID-19) from standard-of-care chest …

Enhanced whale optimization algorithm for medical feature selection: A COVID-19 case study

MH Nadimi-Shahraki, H Zamani, S Mirjalili - Computers in biology and …, 2022 - Elsevier
The whale optimization algorithm (WOA) is a prominent problem solver which is broadly
applied to solve NP-hard problems such as feature selection. However, it and most of its …

Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets

SA Harmon, TH Sanford, S Xu, EB Turkbey… - Nature …, 2020 - nature.com
Chest CT is emerging as a valuable diagnostic tool for clinical management of COVID-19
associated lung disease. Artificial intelligence (AI) has the potential to aid in rapid evaluation …

[HTML][HTML] Adoption of digital technologies in health care during the COVID-19 pandemic: systematic review of early scientific literature

D Golinelli, E Boetto, G Carullo, AG Nuzzolese… - Journal of medical …, 2020 - jmir.org
Background The COVID-19 pandemic is favoring digital transitions in many industries and in
society as a whole. Health care organizations have responded to the first phase of the …

Review of artificial intelligence techniques in imaging data acquisition, segmentation, and diagnosis for COVID-19

F Shi, J Wang, J Shi, Z Wu, Q Wang… - IEEE reviews in …, 2020 - ieeexplore.ieee.org
The pandemic of coronavirus disease 2019 (COVID-19) is spreading all over the world.
Medical imaging such as X-ray and computed tomography (CT) plays an essential role in …

Blockchain-federated-learning and deep learning models for covid-19 detection using ct imaging

R Kumar, AA Khan, J Kumar, NA Golilarz… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
With the increase of COVID-19 cases worldwide, an effective way is required to diagnose
COVID-19 patients. The primary problem in diagnosing COVID-19 patients is the shortage …

Multi-task deep learning based CT imaging analysis for COVID-19 pneumonia: Classification and segmentation

A Amyar, R Modzelewski, H Li, S Ruan - Computers in biology and …, 2020 - Elsevier
This paper presents an automatic classification segmentation tool for helping screening
COVID-19 pneumonia using chest CT imaging. The segmented lesions can help to assess …

Predicting the growth and trend of COVID-19 pandemic using machine learning and cloud computing

S Tuli, S Tuli, R Tuli, SS Gill - Internet of things, 2020 - Elsevier
The outbreak of COVID-19 Coronavirus, namely SARS-CoV-2, has created a calamitous
situation throughout the world. The cumulative incidence of COVID-19 is rapidly increasing …

A fully automatic deep learning system for COVID-19 diagnostic and prognostic analysis

S Wang, Y Zha, W Li, Q Wu, X Li, M Niu… - European …, 2020 - Eur Respiratory Soc
Coronavirus disease 2019 (COVID-19) has spread globally, and medical resources become
insufficient in many regions. Fast diagnosis of COVID-19 and finding high-risk patients with …