Journal Information
Applied Soft Computing
http://www.journals.elsevier.com/applied-soft-computing/
Impact Factor:
5.472
Publisher:
Elsevier
ISSN:
1568-4946
Viewed:
14927
Tracked:
26
Call For Papers
Applied Soft Computing is an international journal promoting an integrated view of soft computing to solve real life problems. Soft computing is a collection of methodologies, which aim to exploit tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low solution cost. The focus is to publish the highest quality research in application and convergence of the areas of Fuzzy Logic, Neural Networks, Evolutionary Computing, Rough Sets and other similar techniques to address real world complexities.

Applied Soft Computing is a rolling publication: articles are published as soon as the editor-in-chief has accepted them. Therefore, the web site will continuously be updated with new articles and the publication time will be short.

Major Topics:

The scope of this journal covers the following soft computing and related techniques, interactions between several soft computing techniques, and their industrial applications:

• Fuzzy Computing
• Neuro Computing
• Evolutionary Computing
• Probabilistic Computing
• Immunological Computing
• Hybrid Methods
• Rough Sets
• Chaos Theory
• Particle Swarm
• Ant Colony
• Wavelet
• Morphic Computing

The application areas of interest include but are not limited to:

• Decision Support
• Process and System Control
• System Identification and Modelling
• Engineerin Design Optimisation
• Signal or Image Processing
• Vision or Pattern Recognition
• Condition Monitoring
• Fault Diagnosis
• Systems Integration
• Internet Tools
• Human-Machine Interface
• Time Series Prediction
• Robotics
• Motion Control and Power Electronics
• Biomedical Engineering
• Virtual Reality
• Reactive Distributed AI
• Telecommunications
• Consumer Electronics
• Industrial Electronics
• Manufacturing Systems
• Power and Energy
• Data Mining
• Data Visualisation
• Intelligent Information Retrieval
• Bio-inspired Systems
• Autonomous Reasoning
• Intelligent Agents
• Multi-objective Optimisation
• Process Optimisation
• Agricultural Machinery and Produce
• Nano and Micro-systems
Last updated by Dou Sun in 2021-03-07
Special Issues
Special Issue on Fuzzy Systems for Biomedical Science in Healthcare
Submission Date: 2021-11-30

Scope of the issue The world issues to deal with the pandemic caused by the pathogen SARS-CoV-2 has urgently posed the need of rethinking the available resources to combat a health crisis of this dimensions. Innovation in healthcare needs to be accelerated to address the health problems of our time and the future. Biomedical and healthcare data are available in different formats, including numeric, textual reports, images, and the data may come from different sources. A major challenge in biomedical science and healthcare involves coping with the uncertainty, imprecision and incompleteness. Such uncertainties make it difficult to develop useful models, algorithms, systems, and realizing their successful applications. Although the current research in this field has shown promising results, there is an urgent need to explore novel data-driven knowledge discovery and analytics methods in clinical research to improve epidemic monitoring and healthcare delivery as a whole. Intelligent medicine and healthcare decision support systems have become an emerging research topic since they can be applied for disease diagnostics and/or prevention, follow-up monitoring, defining treatment pathways, clinical decision support etc. Despite the significant recent advances in medicine and healthcare data analysis, there are substantial research challenges and open questions to be explored. These demand further and deeper investigations to develop more useful decision-making systems that are capable of dealing with randomness, imprecision, volume, vagueness, incompleteness, and missing values along with efficient handling of variety, velocity and (abundant or lacking) volume of biomedical data. Compared to the traditional decision support techniques, the representation of fuzzy linguistic terms based on soft computing provides a straightforward framework for building more understandable, imprecision-aware clinical systems. As opposed to systems powered by statistical reasoning only, fuzzy biomedical systems cater a way of building models that encode the imprecise conceptual semantics of a health problem, not just for doing analytics, but also to embrace its interpretability. Thus, designing an efficient and effective fuzzy system to deal with uncertainty is an emerging and promising topic to improve reasoning and intelligent monitoring, control, diagnostic and treatment in biomedical science in healthcare. Topics In this special issue we will consider submissions in that deal with innovative research works that face contemporary research issues of biomedical engineering in healthcare. Articles that are not innovative enough in their clinical research questions and applications will not be considered for publication in this special issue. The topics include but are not limited to: Fuzzy systems for predicting and monitoring the spread of epidemic diseases Fuzzy systems for measuring the damage of the epidemic disease IT2 fuzzy sets for uncertain healthcare datasets Fuzzy approaches for neuroimaging and functional brain imaging processing of COVID-19 Fuzzy learning models for feature extraction of COVID-19 Fuzzy medicine and healthcare data mining based on the Hadoop or Spark platforms Fuzzy system for patient planning and health services Multi-objective evolutionary and adaptive fuzzy systems for handling epidemic disease Fuzzy models for medical image classification/ diagnosis /recognition Fuzzy data mining for brain-machine interfaces and medical signal analysis Fuzzy classification for multi-modality image fusion for analysis, diagnosis, and intervention Real-world applications of fuzzy system for future challenges of COVID-19
Last updated by Dou Sun in 2021-02-11
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