USE OF ARTIFICIAL INTELLIGENCE IN HISTOPATHOLOGICAL INTERPRETATION - A MINI REVIEW
DOI:
https://doi.org/10.56501/intjhistopatholinterpret.v12i1.883Keywords:
Artificial intelligence, AI, Pathology, Histopathology, InterpretationAbstract
The accuracy of artificial intelligence (AI) in medicine, particularly pathology, has improved significantly, but little is known about how much these algorithms will influence pathologists' decisions in practice.
Most developing-country laboratories lack resources such as whole-slide scanning and digital microscopes. They are unable to manage massive volumes of data due to severe budgetary restrictions and a lack of resources. Because of these limitations, valuable data cannot be kept or used appropriately.
This review attempts to describe the role of AI in histopathological interpretation.
References
Zhou W, Deng Z, Liu Y, Shen H, Deng H, Xiao H. Global Research Trends of Artificial Intelligence on Histopathological Images: A 20-Year Bibliometric Analysis. Int J Environ Res Public Health. 2022 Sep 15;19(18):11597. doi: 10.3390/ijerph191811597. PMID: 36141871; PMCID: PMC9517580.
Cui, M., Zhang, D.Y. Artificial intelligence and computational pathology. Lab Invest 101, 412–422 (2021). https://doi.org/10.1038/s41374-020-00514-0
Yoshida H, Kiyuna T. Requirements for implementation of artificial intelligence in the practice of gastrointestinal pathology. World J Gastroenterol. 2021 Jun 7;27(21):2818-2833. doi: 10.3748/wjg.v27.i21.2818. PMID: 34135556; PMCID: PMC8173389.
Thomas LB, Mastorides SM, Viswanadhan NA, Jakey CE, Borkowski AA. Artificial Intelligence: Review of Current and Future Applications in Medicine. Fed Pract. 2021 Nov;38(11):527-538. doi: 10.12788/fp.0174. PMID: 35136337; PMCID: PMC8815615.
Ahmad Z, Rahim S, Zubair M, Abdul-Ghafar J. Artificial intelligence (AI) in medicine, current applications and future role with special emphasis on its potential and promise in pathology: present and future impact, obstacles including costs and acceptance among pathologists, practical and philosophical considerations. A comprehensive review. Diagn Pathol. 2021 Mar 17;16(1):24. doi: 10.1186/s13000-021-01085-4. PMID: 33731170; PMCID: PMC7971952.
Meyer J, Khademi A, Têtu B, Han W, Nippak P, Remisch D. Impact of artificial intelligence on pathologists' decisions: an experiment. J Am Med Inform Assoc. 2022 Sep 12;29(10):1688-1695. doi: 10.1093/jamia/ocac103. PMID: 35751441; PMCID: PMC9471707.
Jiang Y, Yang M, Wang S, Li X, Sun Y. Emerging role of deep learning-based artificial intelligence in tumor pathology. Cancer Commun (Lond). 2020 Apr;40(4):154-166. doi: 10.1002/cac2.12012. Epub 2020 Apr 11. PMID: 32277744; PMCID: PMC7170661.
Zehra T, Parwani A, Abdul-Ghafar J, Ahmad Z. A suggested way forward for adoption of AI-Enabled digital pathology in low resource organizations in the developing world. Diagn Pathol. 2023 May 18;18(1):68. doi: 10.1186/s13000-023-01352-6. PMID: 37202805; PMCID: PMC10193335.
King H, Wright J, Treanor D, Williams B, Randell R. What Works Where and How for Uptake and Impact of Artificial Intelligence in Pathology: Review of Theories for a Realist Evaluation. J Med Internet Res. 2023 Apr 24;25:e38039. doi: 10.2196/38039. PMID: 37093631; PMCID: PMC10167589.
Alami H, Rivard L, Lehoux P, Hoffman SJ, Cadeddu SBM, Savoldelli M, Samri MA, Ag Ahmed MA, Fleet R, Fortin JP. Artificial intelligence in health care: laying the Foundation for Responsible, sustainable, and inclusive innovation in low- and middle-income countries. Global Health. 2020 Jun 24;16(1):52. doi: 10.1186/s12992-020-00584-1. PMID: 32580741; PMCID: PMC7315549.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Karthikeyan Ramalingam
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
