Integration of Neuro-Fuzzy Systems in Medical Diagnostics and Data Security - A Review

Senivarapu Ankit Reddy; Dr. Vustelamuri Padmavathi

doi:10.32628/IJSRSET24115113

Authors

Senivarapu Ankit Reddy Student of B.Tech in Computer science ,Manipal University, Jaipur, Rajasthan, India Author
Dr. Vustelamuri Padmavathi Associate Professor of Chemistry, Neil Gogte Institute of Technology, Kachavanisingaram, Uppal, Hyderabad, Telangana, India Author

DOI:

https://doi.org/10.32628/IJSRSET24115113

Keywords:

Adaptive Neuro-Fuzzy Systems, Deep Neuro-Fuzzy Systems, Medical IoT, Cloud Security, Healthcare Diagnostics, Fuzzy Logic, Machine Learning

Abstract

Adaptive Neuro-Fuzzy Systems (ANFS) have become increasingly prevalent in a variety of fields due to their ability to process complex and uncertain data with high accuracy. This research article reviews three major contributions of ANFS: their application in deep neuro-fuzzy systems (DNFS) for healthcare and industrial systems, neuro-fuzzy logic controllers for paralysis estimation, and ANFIS-based solutions for secure cloud storage in medical IoT (MIoT). The findings emphasize the importance of ANFS in improving decision-making, diagnosis, and data security. This paper concludes with a discussion on challenges, future research directions, and the need for optimization in real-time applications.

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