Poalelungi Diana Gina, Neagu Anca Iulia, Fulga Ana, Neagu Marius, Tutunaru Dana, Nechita Aurel, Fulga Iuliu
Faculty of Medicine and Pharmacy, Dunarea de Jos University of Galati, 35 AI Cuza St., 800010 Galati, Romania.
Saint Apostle Andrew Emergency County Clinical Hospital, 177 Brailei St., 800578 Galati, Romania.
J Pers Med. 2024 Jun 27;14(7):693. doi: 10.3390/jpm14070693.
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.
人工智能（AI）是我们这个时代的现实，它已在包括医学在内的所有领域成功实施。作为一个相对较新的领域，所有努力都致力于创建适用于大多数医学专业的算法。病理学作为精准医学最重要的关注领域之一，在人工智能算法的开发和实施中受到了极大关注。这种关注对于实现准确诊断尤为重要。此外，免疫组织化学（IHC）在病理学中作为一种辅助诊断工具。通过应用深度学习（DL）和机器学习（ML）算法来评估和分析免疫组织化学标志物，它可以得到进一步增强。这些进展有助于确定靶向治疗方法和预后分层。本文探讨了用于免疫组织化学分析的各种人工智能软件程序和平台的应用与整合。文章最后强调了这些技术在乳腺癌、前列腺癌、肺癌、黑素细胞增殖和血液疾病等病理学中的应用。此外，它强调了进一步创新诊断算法以协助医生进行诊断过程的必要性。
