Deep-Precognitive Diagnosis: Preventing Future Pandemics by Novel Disease Detection With Biologically-Inspired Conv-Fuzzy Network-Reference-Cited by-同舟云学术

Deep-Precognitive Diagnosis: Preventing Future Pandemics by Novel Disease Detection With Biologically-Inspired Conv-Fuzzy Network

Author:

Chharia Aviral¹^ORCID,Upadhyay Rahul²^ORCID,Kumar Vinay²^ORCID,Cheng Chao³^ORCID,Zhang Jing⁴,Wang Tianyang⁵^ORCID,Xu Min⁶^ORCID

Affiliation:

1. Mechanical Engineering Department, Thapar Institute of Engineering and Technology, Patiala, Punjab, India

2. Electronics and Communication Engineering Department, Thapar Institute of Engineering and Technology, Patiala, Punjab, India

3. Department of Medicine, Baylor College of Medicine, Houston, TX, USA

4. Department of Computer Science, University of California at Irvine, Irvine, CA, USA

5. Department of Computer Science and Information Technology, Austin Peay State University, Clarksville, TN, USA

6. Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA

Funder

U.S. National Institutes of Health

U.S. National Science Foundation

Mark Foundation for Cancer Research

AMD COVID-19 High-Performance Computing (HPC) Fund

U.S. NIH

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

Reference86 articles.

1. COVIDX-net: A framework of deep learning classifiers to diagnose COVID-19 in X-ray images;el-din hemdan;arXiv 2003 11055,2020

4. MobileNets: Efficient convolutional neural networks for mobile vision applications;howard;arXiv 1704 04861,2017

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