4Detecting Healthcare Issues Using a Neuro-Fuzzy Classifier
D. Saravanan1*, R. Parthiban2, G. Arunkumar3, D. Suganthi4, Revathi R.5 and U. Palani6
1Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai, India
2Department of Computer Science and Engineering, IFET College of Engineering, Villupuram, India
3Department of Computer Science & Engineering, Madanapalle Institute of Technology & Science, Madanapalle, Andhra Pradesh, India
4Department of Computer Science, Saveetha College of Liberal Arts and Sciences, SIMATS, Thandalam, Chennai, India
5Department of Computer Science, Karpagam Academy of Higher Education, Coimbatore, India
6Department of ECE, IFET College of Engineering, Villupuram, India
Abstract
In the healthcare industry, the use of medical imaging for diagnosis, treatment planning, and monitoring disease development is increasing. In reality, medical imaging handles data that have a solid structural character and include ambiguous, lost, vague, complimentary, conflicting, redundant, contradictory, and distorted information. The understanding of any image often involves the similarity of the content retrieved from the image using presto red models. The development of fuzzy pattern recognition-based medical imaging, which aids in resolving diagnostic and visualization problems in medicine, has drawn more attention. Medical imaging is continuously subject to flaws, some of which may cause segmentation mistakes. The efficiency ...
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