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COVID-19 diagnosis using AI
TopicLeading institutions, researchers & key papers
This cluster of papers focuses on the application of deep learning, particularly convolutional neural networks, in medical imaging for the detection and diagnosis of COVID-19, pneumonia, and other thoracic diseases using chest X-ray and CT scan images. The research explores the use of artificial intelligence, transfer learning, and image-based deep learning techniques to develop automated systems for accurate medical diagnoses.
410
Works
IDs:OpenAlex
How has COVID-19 diagnosis using AI's publication output changed over time?
ScholarIQpublication output · 2016–2023
Output grew0% over the shown period — from 1 works in 2016 to 1 in 2023.
1
11
2
1
2016202020212023
What are the most-cited papers on COVID-19 diagnosis using AI?
ScholarIQmost cited works
Can AI Help in Screening Viral and COVID-19 Pneumonia?
Muhammad E. H. Chowdhury, Tawsifur Rahman, Amith Khandakar, Rashid Mazhar, Muhammad Abdul Kadir, Zaid Bin Mahbub, Khandaker Reajul Islam, Muhammad Salman Khan, Atif Iqbal, Nasser Al Emadi, Mamun Bin Ibne Reaz, Mohammad Tariqul Islam
IEEE Access. 20201,922 CitationsOPEN ACCESS
Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neural Network
Marios Anthimopoulos, Stergios Christodoulidis, Lukas Ebner, Andreas Christe, Stavroula Mougiakakou
S58069681. 20161,335 CitationsOPEN ACCESS
Deep learning-enabled medical computer vision
Andre Esteva, Katherine Chou, Serena Yeung, Nikhil Naik, Ali Madani, Ali Mottaghi, Yun Liu, Eric J. Topol, Jeff Dean, Richard Socher
npj Digital Medicine. 20211,331 CitationsOPEN ACCESS
Exploring the effect of image enhancement techniques on COVID-19 detection using chest X-ray images
Tawsifur Rahman, Amith Khandakar, Yazan Qiblawey, Anas Tahir, Serkan Kıranyaz, Saad Bin Abul Kashem, Mohammad Tariqul Islam, Somaya Al Maadeed, Susu M. Zughaier, Muhammad Salman Khan, Muhammad E. H. Chowdhury
S44278595. 20211,128 CitationsOPEN ACCESS
Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography
Kang Zhang, Xiaohong Liu, Jun Shen, Zhihuan Li, Ye Sang, Xingwang Wu, Yunfei Zha, Wenhua Liang, Chengdi Wang, Ke Wang, Linsen Ye, Ming Gao, Zhongguo Zhou, Liang Li, Jin Wang, Zehong Yang, Huimin Cai, Jie Xu, Lei Yang, Wenjia Cai, W. Xu, Shaoxu Wu, Wei Zhang, Shanping Jiang, Lianghong Zheng, Xuan Zhang, Li Wang, Lu Liu, Jiaming Li, Haiping Yin, Winston Wang, Oulan Li, Charlotte Zhang, Liang Liang, Tao Wu, Ruiyun Deng, Wei Kang, Yong Zhou, Ting Chen, Johnson Yiu‐Nam Lau, Manson Fok, Jianxing He, Tianxin Lin, Weimin Li, Guangyu Wang
S110447773. 2020963 CitationsOPEN ACCESS
Where is COVID-19 diagnosis using AI research published, and who funds it?
ScholarIQvenues & funding sources
TOP JOURNALS
TOP FUNDERS
National Science Foundation—
NIH—
Wellcome Trust—
European Research Council—
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How much of the research on COVID-19 diagnosis using AI is open access?
ScholarIQopen access share
87%OPEN ACCESS
Gold
33%
Green
33%
Hybrid
7%
Bronze
13%
Closed
13%
Related on ScholarIQ
Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning
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Can AI Help in Screening Viral and COVID-19 Pneumonia?
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The COVID-19 pandemic
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Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neural Network
Paper
Deep learning-enabled medical computer vision
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Exploring the effect of image enhancement techniques on COVID-19 detection using chest X-ray images
Paper