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The soft computing-based approach to investigate allergic diseases: a systematic review
Gennaro Tartarisco1, Alessandro Tonacci2, Paola Lucia Minciullo3
1Messina Unit, National Research Council of Italy (CNR)-Institute of Applied Science and Intelligent System (ISASI), Messina, Italy.
Clinical and Molecular Allergy : CMA
|April 18, 2017
Summary
Soft computing approaches show promise for analyzing allergic diseases, achieving 86.5% accuracy in a systematic review. These computational methods excel with complex data, offering new insights beyond traditional statistics.
Area of Science:
- Allergy and immunology
- Computational intelligence
- Data science
Background:
- Early identification of inflammatory markers is crucial for managing allergic diseases like asthma and atopic dermatitis.
- Traditional statistical methods dominate allergy research, but computational techniques offer new potential.
- Soft computing approaches present a promising alternative for analyzing complex allergic disease data.
Purpose of the Study:
- To systematically review soft computing techniques (artificial neural networks, support vector machines, Bayesian networks, fuzzy logic) for allergic diseases.
- To evaluate the performance of these computational methods in the context of allergy research.
- To identify the potential of soft computing in advancing the understanding and diagnosis of allergic conditions.
Main Methods:
- Systematic literature review following PRISMA guidelines.
- Protocol registered in PROSPERO (CRD42016038894).
- Searched PubMed and ScienceDirect databases from September 1990 to April 2016.
Main Results:
- Included 27 studies on allergic diseases and soft computing.
- Achieved an overall accuracy of 86.5%, with a focus on asthma.
- Soft computing is effective for big data analysis, handling uncertainty, and complex relationships.
Conclusions:
- Soft computing approaches demonstrate significant potential for allergic disease research.
- These methods can provide valuable support in data-scarce or complex scenarios.
- Further application of soft computing could lead to breakthroughs in understanding various allergic diseases beyond asthma.