• Jafar Ali Ibrahim Syed Masood, N S Kalyan Chakravarthy, Omar H Abd-Elkader, Anis Ahamed, Alhaf Malik Kaja Mohaideen, and Vijayan Sugumaran.
• Department of Internet of Things, School of Computer Science and Engineering, Vellore Institute of Technology, Vellore 632 014, Tamilnadu, India. Electronic address: jafarali.s@vit.ac.in.
• Prev Med. 2023 Sep 1; 174: 107620107620.

AbstractCurrently, the risks posed by bacteria are becoming increasingly important. It now appears that the cell wall of Anammox image bacteria is very different from what has been generally considered for many years. Not every textbook contains the peptidoglycan on the cell wall of Anammox image bacteria - the sugar-protein chain that strengthens the cells of most bacteria. Most researchers in this Anammox image bacteria diseased identification wanted to find out what gave the Anammox image cell its stability. It used powerful cryo-electron microscopes to examine the bacterial cell wall and find the exact structure of the peptidoglycan. A new algorithm is proposed to discover that Anammox image bacteria contain peptidoglycan, which completes a theory in microbiology. The identification of different diseases is listed, and the proposed model compares the exact results while comparing the parameters like accuracy, precision, recall, and F1-Score. Keywords: Anammox image bacteria, cell wall, cell stability, cryo-electron, microscope images, accuracy, precision, recall, F1-score.Copyright © 2023 Elsevier Inc. All rights reserved.

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