Computational and Mathematical Methods in Medicine

Advanced Computational Intelligence Methods and Ubiquitous Computing Model for Combating Infectious Disease


Publishing date
01 Aug 2021
Status
Closed
Submission deadline
26 Mar 2021

Lead Editor

1The Affiliated Changshu Hospital of Soochow University, Suzhou, China

2Macquarie University, Sydney, Australia

3Fondazione Bruno Kessler, Povo, Italy

This issue is now closed for submissions.
More articles will be published in the near future.

Advanced Computational Intelligence Methods and Ubiquitous Computing Model for Combating Infectious Disease

This issue is now closed for submissions.
More articles will be published in the near future.

Description

The fight against infectious diseases is one of the greatest challenges faced by mankind. Infectious diseases pose a serious threat to human life across the entire globe and can also have an unprecedented impact on our day-to-day lives and the global economy. Computational intelligence technology and ubiquitous computing models have also attracted a lot of attention in recent years. Researchers have invested a lot of time and energy to analyze the source of epidemics and predict the spread of epidemics using computational intelligence technology and ubiquitous computing models.

Recently, many computational intelligence technologies have appeared, such as multi-view learning, transfer learning and deep learning, and so on. Multi-view learning is the branch of machine learning concerned with the analysis of multi-modal data, i.e. patterns represented by different sets of features extracted from multiple data sources. Transfer learning makes use of data or knowledge gained in solving one problem to help solve a different, albeit related problem. Deep learning is a rapidly advancing field in medical image processing, natural language understanding, and bioinformatics in recent years. In addition, with the development of ubiquitous computing, ubiquitous medical devices make it possible to monitor patients in their work, domiciliary, and institutional settings as well as enabling peripatetic clinicians to access clinical information and services for treatment of the patient outside of clinical organizations. How to obtain advanced models with both intelligence and perception by integrating emerging computational intelligence technology into the ubiquitous computing model, and solving problems such as source tracking or propagation prediction of infectious diseases, is a big challenge in current related technologies.

This Special Issue will focus on the advanced computational intelligence technology and ubiquitous computing for severity assessment and classification of infectious disease, infectious disease intelligent diagnosis, new feature extraction and representation of infectious disease data, and large-scale infectious disease data analysis. We invite authors to contribute original research or review articles in this field.

Potential topics include but are not limited to the following:

  • Computational intelligence and ubiquitous computing for severity assessment and classification of infectious disease
  • Computational intelligence and ubiquitous computing for infectious disease intelligent diagnosis
  • Computational intelligence and ubiquitous computing for multimedia-based infectious disease intelligent diagnosis
  • New feature extraction and representation algorithms for the detection and diagnosis of infectious disease
  • Knowledge discovery and pattern recognition from large-scale infectious disease data

Articles

  • Special Issue
  • - Volume 2021
  • - Article ID 6648959
  • - Research Article

Stability and Hopf Bifurcation Analysis of a Vector-Borne Disease Model with Two Delays and Reinfection

Yanxia Zhang | Long Li | ... | Yanjun Liu
  • Special Issue
  • - Volume 2021
  • - Article ID 5528144
  • - Review Article

An Overview of Deep Learning Techniques on Chest X-Ray and CT Scan Identification of COVID-19

Woan Ching Serena Low | Joon Huang Chuah | ... | Khin Wee Lai
  • Special Issue
  • - Volume 2021
  • - Article ID 6676987
  • - Research Article

Clinical Characteristics and Early Interventional Responses in Patients with Severe COVID-19 Pneumonia

Susu He | Lina Fang | ... | Dinghai Luo
  • Special Issue
  • - Volume 2021
  • - Article ID 9940148
  • - Research Article

Expression-EEG Bimodal Fusion Emotion Recognition Method Based on Deep Learning

Yu Lu | Hua Zhang | ... | Jing Li
  • Special Issue
  • - Volume 2021
  • - Article ID 9967592
  • - Research Article

Expression EEG Multimodal Emotion Recognition Method Based on the Bidirectional LSTM and Attention Mechanism

Yifeng Zhao | Deyun Chen
  • Special Issue
  • - Volume 2021
  • - Article ID 6633755
  • - Research Article

PSSPNN: PatchShuffle Stochastic Pooling Neural Network for an Explainable Diagnosis of COVID-19 with Multiple-Way Data Augmentation

Shui-Hua Wang | Yin Zhang | ... | Yu-Dong Zhang
  • Special Issue
  • - Volume 2021
  • - Article ID 8853787
  • - Research Article

Decision Model for Allocation of Intensive Care Unit Beds for Suspected COVID-19 Patients under Scarce Resources

Eduarda Asfora Frej | Lucia Reis Peixoto Roselli | ... | Adiel Teixeira de Almeida
  • Special Issue
  • - Volume 2020
  • - Article ID 8845459
  • - Research Article

How to Determine the Early Warning Threshold Value of Meteorological Factors on Influenza through Big Data Analysis and Machine Learning

Hui Ge | Debao Fan | ... | Xu Yang
  • Special Issue
  • - Volume 2020
  • - Article ID 8823861
  • - Research Article

A Multifeature Extraction Method Using Deep Residual Network for MR Image Denoising

Li Yao
Computational and Mathematical Methods in Medicine
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Acceptance rate32%
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Acceptance to publication39 days
CiteScore3.500
Impact Factor2.238
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