This bibliographic study covers Artificial Intelligence (AI)theory and its applications from the healthcare field and in particular from the discipline of pathology. This review includes basics of AI, supervised and unsupervised machine learning (ML), various supervised ML algorithms, and their applications in healthcare and pathology. Digital Pathology with Deep Machine Learning is more advantageous over traditional pathology that is based on ‘physical slide on a physical microscope’. However, various implementation challenges of cost, data quality, multicenter validation, bias, and regulatory approval issues for AI in clinical practice still remain, which are also described in this study.

How to Cite
BUCH, ROHAN KULKARNI, Archana. Artificial Intelligence (AI) in Pathology – A Summary and Challenges. Global Journal of Medical Research, [S.l.], feb. 2021. ISSN 2249-4618. Available at: <https://medicalresearchjournal.org/index.php/GJMR/article/view/2371>. Date accessed: 15 may 2021. doi: https://doi.org/10.34257/GJMRKVOL21IS2PG23.

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