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Review

Revolutionizing Pathology with Artificial Intelligence: Innovations in Immunohistochemistry

1
Faculty of Medicine and Pharmacy, Dunarea de Jos University of Galati, 35 AI Cuza St., 800010 Galati, Romania
2
Saint Apostle Andrew Emergency County Clinical Hospital, 177 Brailei St., 800578 Galati, Romania
3
Saint John Clinical Emergency Hospital for Children, 800487 Galati, Romania
*
Authors to whom correspondence should be addressed.
J. Pers. Med. 2024, 14(7), 693; https://doi.org/10.3390/jpm14070693
Submission received: 12 June 2024 / Revised: 25 June 2024 / Accepted: 26 June 2024 / Published: 27 June 2024
(This article belongs to the Section Clinical Medicine, Cell, and Organism Physiology)

Abstract

Artificial intelligence (AI) is a reality of our times, and it has been successfully implemented in all fields, including medicine. As a relatively new domain, all efforts are directed towards creating algorithms applicable in most medical specialties. Pathology, as one of the most important areas of interest for precision medicine, has received significant attention in the development and implementation of AI algorithms. This focus is especially important for achieving accurate diagnoses. Moreover, immunohistochemistry (IHC) serves as a complementary diagnostic tool in pathology. It can be further augmented through the application of deep learning (DL) and machine learning (ML) algorithms for assessing and analyzing immunohistochemical markers. Such advancements can aid in delineating targeted therapeutic approaches and prognostic stratification. This article explores the applications and integration of various AI software programs and platforms used in immunohistochemical analysis. It concludes by highlighting the application of these technologies to pathologies such as breast, prostate, lung, melanocytic proliferations, and hematologic conditions. Additionally, it underscores the necessity for further innovative diagnostic algorithms to assist physicians in the diagnostic process.
Keywords: artificial intelligence; computer-assisted image analysis; computer-aided diagnosis; pathology; digital pathology; immunohistochemistry artificial intelligence; computer-assisted image analysis; computer-aided diagnosis; pathology; digital pathology; immunohistochemistry

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MDPI and ACS Style

Poalelungi, D.G.; Neagu, A.I.; Fulga, A.; Neagu, M.; Tutunaru, D.; Nechita, A.; Fulga, I. Revolutionizing Pathology with Artificial Intelligence: Innovations in Immunohistochemistry. J. Pers. Med. 2024, 14, 693. https://doi.org/10.3390/jpm14070693

AMA Style

Poalelungi DG, Neagu AI, Fulga A, Neagu M, Tutunaru D, Nechita A, Fulga I. Revolutionizing Pathology with Artificial Intelligence: Innovations in Immunohistochemistry. Journal of Personalized Medicine. 2024; 14(7):693. https://doi.org/10.3390/jpm14070693

Chicago/Turabian Style

Poalelungi, Diana Gina, Anca Iulia Neagu, Ana Fulga, Marius Neagu, Dana Tutunaru, Aurel Nechita, and Iuliu Fulga. 2024. "Revolutionizing Pathology with Artificial Intelligence: Innovations in Immunohistochemistry" Journal of Personalized Medicine 14, no. 7: 693. https://doi.org/10.3390/jpm14070693

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