Advancements and applications of AI technologies in pathology: a scoping review
| Autor: | Iira Salo, Lovisa Nordlund, Linnea Eklund, Joseph Ho, Mikael Soini, Darshan Kumar, Joe Yeong, Frank Guan, Eija Metsälä |
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| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, Vol 12, Iss 1 (2024) |
| Druh dokumentu: | article |
| ISSN: | 21681163 2168-1171 2168-1163 |
| DOI: | 10.1080/21681163.2024.2396595 |
| Popis: | The benefits of AI in pathology are demonstrated by the growing potential of diagnostic accuracy and efficiency in tissue segmentation, cancer detection and grading. In this scoping review, we studied how artificial intelligence (AI) technologies have been developed for usage in pathology. In the study, a literature search on databases and publisher portals PubMed, ScienceDirect, ProQuest, and CINAHL was conducted to collect peer-reviewed studies published between 2019 and 2023. Then after a thorough database search, 57 articles covering the topic were included out of 19 185 potential ones and were categorised into groups by their main purposes, such as pre-processing, segmentation, analysis, and prediction. The findings demonstrate that AI technologies like deep learning and convolutional neural networks (CNNs) enhance medical imaging for tissue segmentation and cancer detection by reducing human error and variability. |
| Databáze: | Directory of Open Access Journals |
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