Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)

Precision-Driven Pneumonia Diagnosis: Integrating Adaptive Neuro-Fuzzy Inference System (ANFIS) with High-Dimensional Data Analysis

Authors
Veera Swamy Pittala1, Uppalapati Asritha1, *, Kasthala Ashok Babu1, Puritipati Harsha Vardhan Reddy1
1Department of Computer Science and Engineering, Lakireddy Bali Reddy College Engineering, Mylavaram, India
*Corresponding author. Email: asrithareddyuppalapati2003@gmail.com
Corresponding Author
Uppalapati Asritha
Available Online 30 July 2024.
DOI
10.2991/978-94-6463-471-6_74How to use a DOI?
Keywords
Adaptive Learning; Clinical Data Analysis; Diagnostic Accuracy; Fuzzy Logic; High-Dimensional Data; Neuro-Fuzzy Systems; Pneumonia Diagnosis; ROC-AUC
Abstract

This research paper introduces a transformative approach to diagnosing pneumonia through an Adaptive Neuro-Fuzzy Inference System (ANFIS) tailored for high-dimensional clinical data. The ANFIS model fuses the interpretive strengths of fuzzy logic with the adaptive properties of neural networks to process intricate patient data. Our comprehensive evaluation across numerous clinical datasets demonstrates an unprecedented diagnostic accuracy rate exceeding 95%, a precision rate above 90%, and a recall rate equally robust, culminating in an F1 score of 0.92. These metrics, coupled with a ROC-AUC value of 0.98, underscore the model’s exceptional capability in discriminating between the nuanced presentations of pneumonia and healthy cases. The findings signal a significant advancement in clinical diagnostics, suggesting the ANFIS model’s potential to enhance patient outcomes through precise and reliable pneumonia detection. This integration of neuro-fuzzy systems with machine learning opens new avenues for the development of high-accuracy diagnostic tools, potentially revolutionizing the domain of medical diagnostics and patient care.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)
Series
Advances in Computer Science Research
Publication Date
30 July 2024
ISBN
978-94-6463-471-6
ISSN
2352-538X
DOI
10.2991/978-94-6463-471-6_74How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Veera Swamy Pittala
AU  - Uppalapati Asritha
AU  - Kasthala Ashok Babu
AU  - Puritipati Harsha Vardhan Reddy
PY  - 2024
DA  - 2024/07/30
TI  - Precision-Driven Pneumonia Diagnosis: Integrating Adaptive Neuro-Fuzzy Inference System (ANFIS) with High-Dimensional Data Analysis
BT  - Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)
PB  - Atlantis Press
SP  - 770
EP  - 780
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-471-6_74
DO  - 10.2991/978-94-6463-471-6_74
ID  - Pittala2024
ER  -