Clinical Applications of Artificial Intelligence in Urologic Oncology

Sharif Hosein; Chanan R. Reitblat; Eugene B. Cone; Quoc-Dien Trinh

Disclosures

Curr Opin Urol. 2020;30(6):748-753. 

In This Article

Conclusion

Retrospective data in the form of imaging studies, histopathologic slides, and genomic annotations make the field of urologic oncology low hanging fruit for the adoption of artificial intelligence. Applications for artificial intelligence span diagnosis, prognosis, treatment, and monitoring. Widespread clinical use of artificial intelligence, however, will need to integrate several forms of data into single platforms. Additionally, the data used will need to be abundant, high quality, and representative of the patient population.

Comments

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