International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

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 Volume 10, Issue 12 (December 2023), Pages: 29-41

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 Review Paper

Current trends of artificial intelligence and applications in digital pathology: A comprehensive review

 Author(s): 

 Neelankit Gautam Goswami 1, Shreyas Karnad 1, Niranjana Sampathila 1, *, G. Muralidhar Bairy 1, Krishnaraj Chadaga 2, K. S. Swathi 3

 Affiliation(s):

 1Department of Biomedical Engineering, Manipal Institute of Technology (MIT), Manipal Academy of Higher Education, Manipal, India
 2Department of Computer Science and Engineering, Manipal Institute of Technology (MIT), Manipal Academy of Higher Education, Manipal, India
 3Prasanna School of Public Health, Manipal Academy of Higher Education, Manipal, India

 Full text

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 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0002-3345-360X

 Digital Object Identifier (DOI)

 https://doi.org/10.21833/ijaas.2023.12.004

 Abstract

Digital pathology is a field that blends various techniques for obtaining, analyzing, sharing, and saving information about pathology. This information often comes from digitized microscope slides. Digital pathology also uses artificial intelligence (AI) to help reduce errors made by humans. This review talks about digital pathology and the new techniques linked to it. Instead of traditional microscopes, digital pathology employs virtual microscopy and whole-slide imaging. It marks a major improvement over old pathology methods, which had several problems. Digital methods use computers and machines to solve these issues. The basic process of digital pathology has three parts: the input stage, the analysis stage, and the output stage, which includes storing the information. This review focuses on two main techniques: object detection and its smaller methods, and the use of AI and its specific approaches like explainable AI (XAI) and deep learning. The paper also discusses various deep learning methods, mainly used to detect different types of cancer. It also acknowledges that not every method is perfect, so we discuss various challenges and limitations of digital pathology techniques that need to be solved before these methods can be widely used.

 © 2023 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords

 Artificial intelligence, Digital pathology, Object detection, Digital health

 Article history

 Received 1 July 2023, Received in revised form 11 October 2023, Accepted 9 November 2023

 Acknowledgment 

No Acknowledgment.

 Compliance with ethical standards

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Goswami NG, Karnad S, Sampathila N, Bairy GM, Chadaga K, and Swathi KS (2023). Current trends of artificial intelligence and applications in digital pathology: A comprehensive review. International Journal of Advanced and Applied Sciences, 10(12): 29-41

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 Figures

 Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5 Fig. 6 Fig. 7 Fig. 8 Fig. 9 

 Tables

 Table 1 Table 2 Table 3 Table 4 

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