[
1. Amisha, Malik P, Pathania M, Rathaur VK. Overview of AI in medicine. J Family Med Prim Care, 2019;8(7):2328-2331.10.4103/jfmpc.jfmpc_440_19669144431463251
]Search in Google Scholar
[
2. Hamet P, Tremblay J. AI in medicine. Metabolism, 2017;69S:S36-S40.10.1016/j.metabol.2017.01.01128126242
]Search in Google Scholar
[
3. Mayo RC, Leung J. AI and deep learning - Radiology’s next frontier? Clin Imaging, 2018;49:87-88.10.1016/j.clinimag.2017.11.007
]Search in Google Scholar
[
4. Labovitz DL, Shafner L, Reyes Gil M, Virmani D, Hanina A. Using AI to Reduce the Risk of Nonadherence in Patients on Anticoagulation Therapy. Stroke, 2017;48(5):1416-1419.10.1161/STROKEAHA.116.016281543236928386037
]Search in Google Scholar
[
5. Yu KH, Beam AL, Kohane IS. AI in healthcare. Nat Biomed Eng, 2018;2(10):719-731.10.1038/s41551-018-0305-z
]Search in Google Scholar
[
6. Krittanawong C. The rise of AI and the uncertain future for physicians. Eur J Intern Med, 2018;48:e13-e14.10.1016/j.ejim.2017.06.01728651747
]Search in Google Scholar
[
7. Cocuz IG, Cocuz ME, Niculescu R, et al. The Impact of and Adaptations Due to the COVID-19 Pandemic on the Histopathological Diagnosis of Skin Pathologies, Including Non-Melanocyte and Melanoma Skin Cancers-A Single-Center Study in Romania. Medicina (Kaunas), 2021;57(6):533.10.3390/medicina57060533822697934071770
]Search in Google Scholar
[
8. Krittanawong C. Healthcare in the 21st century. Eur J Intern Med, 2017;38:e17.10.1016/j.ejim.2016.11.00227847141
]Search in Google Scholar
[
9. Bi WL, Hosny A, Schabath MB, et al. AI in cancer imaging: Clinical challenges and applications. CA Cancer J Clin, 2019;69(2):127-157.10.3322/caac.21552
]Search in Google Scholar
[
10. Liang M, Tang W, Xu DM, Jirapatnakul AC, Reeves AP, Henschke CI, Yankelevitz D. Low-Dose CT Screening for Lung Cancer: Computer-aided Detection of Missed Lung Cancers. Radiology, 2016;281(1):279-88.10.1148/radiol.201615006327019363
]Search in Google Scholar
[
11. Peris K, Fargnoli MC, Garbe C, et al. European Dermatology Forum (EDF), the European Association of Dermato-Oncology (EADO) and the European Organization for Research and Treatment of Cancer (EORTC). Diagnosis and treatment of basal cell carcinoma: European consensus-based interdisciplinary guidelines. Eur J Cancer, 2019;118:10-34.10.1016/j.ejca.2019.06.00331288208
]Search in Google Scholar
[
12. He J, Baxter SL, Xu J, Xu J, Zhou X, Zhang K. The practical implementation of AI technologies in medicine. Nat Med, 2019;25(1):30-36.10.1038/s41591-018-0307-0699527630617336
]Search in Google Scholar
[
13. Holzinger A, Langs G, Denk H, Zatloukal K, Müller H. Causability and explainability of AI in medicine. Wiley Interdiscip Rev Data Min Knowl Discov, 2019;9(4):e1312.10.1002/widm.1312701786032089788
]Search in Google Scholar
[
14. Försch S, Klauschen F, Hufnagl P, Roth W. AI in Pathology. Dtsch Arztebl Int, 2021;118(12):194-204.
]Search in Google Scholar
[
15. Matheny ME, Whicher D, Thadaney Israni S. AI in Health Care: A Report From the National Academy of Medicine. JAMA, 2020;323(6):509-510.10.1001/jama.2019.2157931845963
]Search in Google Scholar
[
16. Liu F, Zhou Z, Samsonov A, et al. Deep Learning Approach for Evaluating Knee MR Images: Achieving High Diagnostic Performance for Cartilage Lesion Detection. Radiology, 2018;289(1):160-169.10.1148/radiol.2018172986616686730063195
]Search in Google Scholar
[
17. Bartels R, Dudink J, Haitjema S, Oberski D, van’t Veen A. A Perspective on a Quality Management System for AI/ML-Based Clinical Decision Support in Hospital Care. Front Digit Health, 2022;4:942588.10.3389/fdgth.2022.942588929942535873347
]Search in Google Scholar
[
18. Parwani AV. Next generation diagnostic pathology: use of digital pathology and AI tools to augment a pathological diagnosis. Diagn Pathol, 2019;14(1):138.10.1186/s13000-019-0921-2693373331881972
]Search in Google Scholar
[
19. Mandong BM. Diagnostic oncology: role of the pathologist in surgical oncology--a review article. Afr J Med Med Sci, 2009;38 Suppl 2:81-8.
]Search in Google Scholar
[
20. Amin W, Srintrapun SJ, Parwani AV. Automated whole slide imaging. Expert Opin Med Diagn, 2008;2(10):1173-81.10.1517/17530059.2.10.117323496426
]Search in Google Scholar
[
21. Chen PC, Gadepalli K, MacDonald R, et al. An augmented reality microscope with real-time AI integration for cancer diagnosis. Nat Med, 2019;25(9):1453-1457.10.1038/s41591-019-0539-731406351
]Search in Google Scholar
[
22. Elmore JG, Longton GM, Carney PA, et al. Diagnostic concordance among pathologists interpreting breast biopsy specimens. JAMA, 2015;313(11):1122-32.10.1001/jama.2015.1405451638825781441
]Search in Google Scholar
[
23. Brimo F, Schultz L, Epstein JI. The value of mandatory second opinion pathology review of prostate needle biopsy interpretation before radical prostatectomy. J Urol, 184(1):126-30.10.1016/j.juro.2010.03.02120478583
]Search in Google Scholar
[
24. Campanella G, Hanna MG, Geneslaw L, et al. Clinical-grade computational pathology using weakly supervised deep learning on whole slide images. Nat Med, 2019; 25(8):1301-1309.10.1038/s41591-019-0508-1741846331308507
]Search in Google Scholar
[
25. Bera K, Schalper KA, Rimm DL, Velcheti V, Madabhushi A. AI in digital pathology - new tools for diagnosis and precision oncology. Nat Rev Clin Oncol, 2019;16(11):703-715.10.1038/s41571-019-0252-y688086131399699
]Search in Google Scholar