Intelligent Algorithms_COVID-19: Intelligent Algorithms for Covid-19 Big Data Analytics- Challenges and Recent Advances |
Website | https://easychair.org/cfp/Intelligent_Algorithms_2020 |
Submission link | https://easychair.org/conferences/?conf=intelligentalgorithm |
Submission deadline | November 7, 2020 |
SPECIAL ISSUE ON
Intelligent Algorithms for Covid-19 Big Data Analytics- Challenges and Recent Advances
The most serious issue that concerns the world during this period is the outbreak of the novel Corona virus (COVID-19). The rapid spread of the virus around the world poses a real threat to all countries, as result to that, researchers must pay attention to studying the details of this calamity. COVID-19 symptoms may be similar to other viral chest diseases in some of the symptoms that may cause the doctor’s uncertainty in making the correct diagnosis decision due to the novelty of this virus. The recent diagnosis of COVID-19 is based on real-time reverse-transcriptase polymerase chain reaction (RT-PCR), and regarded as the gold standard for confirmation of infection. It has already been widely recognized that deep learning techniques can potentially have a substantial role in streamlining and accelerating the diagnosis of COVID-19 patients. Numerous open dataset enterprises have been set up over the past weeks to aid the researchers to develop and check methods that could contribute to countering the Corona pandemic. To report the above unique problems in diagnosis of COVID-19, various techniques need to be developed. This special issue focuses on novel deep learning imaging analysis techniques related to COVID-19.
This special section provides a perfect platform to submit manuscripts which discuss about the prospective developments and innovative ideas in deep learning techniques in diagnosis of COVID-19.
The topics of interest include, but are not limited to:
- Deep Learning for the medical diagnosis of COVID-19 and similar diseases
- Neural Network for medical diagnosis of COVID-19 and similar diseases
- Integration of Image Progressing and ML for medical diagnosis of COVID-19 and similar diseases
- Integration of Computer Communication and ML for medical diagnosis of COVID-19 and similar diseases
- Use cases of computer-assisted detection systems for COVID-19 and similar diseases
- COVID-19 patient care and treatment using ML-oriented systems
- Deep Learning Techniques based medical image analyses of COVID-19
- Deep Learning Techniques based COVID-19 diagnostic systems
- Deep Learning Techniques for lung and infection segmentation
- Detection of COVID-19 disease based on Deep Features
- Deep Learning -based CT assessment
- Deep Learning Techniques based on CT images
- Early prediction of COVID-19 based advanced deep learning methods
- Deep Learning Techniques for Tracking COVID-19
- Deep learning Techniques for data mining in COVID-19
- Deep Learning Techniques for managing COVID-19
- Deep learning Techniques for big data analytics in COVID-19
- Deep Learning Techniques for predicting long-term risk of COVID-19
- Deep Learning Systems to Screen Coronavirus Disease
- Novel applications by advanced deep learning for COVID-19
- Emerging networks solutions for improved medical diagnosis of COVID-19 and similar diseases
- Intelligent hardware solutions for medical diagnosis of COVID-19 and similar diseases
- Effective use of computer communication and ML for solving open medical problems
- Next Generation Networks (NGNs) and ML solutions for medical diagnosis
- Artificial Intelligence (AI) assisted techniques for COVID-19 in big data
- Data-driven large scale optimizations for COVID-19
- ML and AI systems analysis, modelling, simulation, and application in COVID-19
Submission Guidelines
**All papers are refereed through a peer review process. Submitted papers should present original, unpublished work, relevant to one of the topics of the Special Issue. All submitted papers will be evaluated on the basis of relevance, the significance of contribution, technical quality, scholarship, and quality of presentation, by at least three independent reviewers.
**All accepted papers will be publish in a good ( web of science) indexed journal. The journal name will be announced once we get approval.
Contact
Dr. Andino Maseleno (Lead Guest Editor)
Institute of Informatics and Computing Energy
Universiti Tenaga Nasional, Malaysia.
Email: andinmaseleno@gmail.com
Google Scholar: https://scholar.google.com/citations?user=HfQ2jGIAAAAJ&hl=en
Dr. Xiaohui Yuan
Department of Computer Science and Engineering, University of North Texas, USA.
Director, Computer Vision and Intelligent Systems Lab, University of North Texas, USA
Email: xiaohui.yuan@unt.edu
Website: http://facultyinfo.unt.edu/faculty-profile?profile=xy0009