Analysis of Q-Factor in FSO-OCDMA using Different Modulation Techniques

  • Cyril Mathew O et al.
Keywords: Mellitus, Diabetes, detection, machine learning, algorithms, classification

Abstract

Introduction: Diabetes Mellitus (DM) was a disease that causes patients' organs to malfunction as a result of uncontrolled diabetes.

Objectives: Early diagnosis and treatment of DM is more beneficial than manual evaluation through an automated process, thanks to recent advances in computer vision  and machine intelligence.

Methods: In this evaluation, six facets of DM acknowledgement, prognosis, and self-management methods are thoroughly analysed and presented, notably DM sets of data, technologies employed in pre-processing, extracting features; recognition through machine learning; classification and prognosis of DM; and smart DM assistant artificial intelligence - based.

Results and conclusion: The preceding research's results and conclusions are interpreted. This study also provides a complete overview of DM diagnosis and self-administration technology, which can be useful to researchers in the field..

Author Biography

Cyril Mathew O et al.

Dr Cyril Mathew O1, Dr Balaji G2, Tamilselvan K3
1,2 Professor & Head, 3Final Year M.E. VLSI Design
1,3Department of Electronics and Communication Engineering
2Department of Mathematics
Al-Ameen Engineering College (Autonomous), Erode – 638 104, Tamilnadu, India.

Published
2024-02-04
Issue
Volume 2024
Section
Regular Issue

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