Artificial Intelligence and Histopathological Diagnosis of Prostate Cancer
| Autor: | Rajendra B. Nerli, Shridhar C. Ghagane, Anil Gavade |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Journal of the Scientific Society, Vol 51, Iss 2, Pp 153-156 (2024) |
| Druh dokumentu: | article |
| ISSN: | 0974-5009 2278-7127 |
| DOI: | 10.4103/jss.jss_118_22 |
| Popis: | As of today, the diagnosis and management of prostate cancer involve the interpretation of data from multiple modalities and tools such as serum prostate-specific antigen levels, magnetic resonance imaging-guided biopsies, genomic biomarkers, and Gleason grading which are used to diagnose, risk stratify, and then monitor patients during respective follow-ups. Artificial intelligence (AI) can allow clinicians to recognize difficult relationships and manage enormous data sets, which is a task that is both extraordinarily difficult and time-consuming for humans. By using AI algorithms and reducing the level of subjectivity, it is possible to use fewer resources while improving the overall efficiency and accuracy in prostate cancer diagnosis and management. In this short review, we have made a case for the use of AI in the histopathological diagnosis of prostate cancer. |
| Databáze: | Directory of Open Access Journals |
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