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Pathomics in urology

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Pathomics in urology. / Schuettfort, Victor M; Pradere, Benjamin; Rink, Michael; Comperat, Eva; Shariat, Shahrokh F.

in: CURR OPIN UROL, Jahrgang 30, Nr. 6, 11.2020, S. 823-831.

Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Review › Forschung

Harvard

Schuettfort, VM, Pradere, B, Rink, M, Comperat, E & Shariat, SF 2020, 'Pathomics in urology', CURR OPIN UROL, Jg. 30, Nr. 6, S. 823-831. https://doi.org/10.1097/MOU.0000000000000813

APA

Schuettfort, V. M., Pradere, B., Rink, M., Comperat, E., & Shariat, S. F. (2020). Pathomics in urology. CURR OPIN UROL, 30(6), 823-831. https://doi.org/10.1097/MOU.0000000000000813

Vancouver

Schuettfort VM, Pradere B, Rink M, Comperat E, Shariat SF. Pathomics in urology. CURR OPIN UROL. 2020 Nov;30(6):823-831. https://doi.org/10.1097/MOU.0000000000000813

Bibtex

@article{0c1811c74db6440b8a70d596322d878e,
title = "Pathomics in urology",
abstract = "PURPOSE OF REVIEW: Pathomics, the fusion of digitalized pathology and artificial intelligence, is currently changing the landscape of medical pathology and biologic disease classification. In this review, we give an overview of Pathomics and summarize its most relevant applications in urology.RECENT FINDINGS: There is a steady rise in the number of studies employing Pathomics, and especially deep learning, in urology. In prostate cancer, several algorithms have been developed for the automatic differentiation between benign and malignant lesions and to differentiate Gleason scores. Furthermore, several applications have been developed for the automatic cancer cell detection in urine and for tumor assessment in renal cancer. Despite the explosion in research, Pathomics is not fully ready yet for widespread clinical application.SUMMARY: In prostate cancer and other urologic pathologies, Pathomics is avidly being researched with commercial applications on the close horizon. Pathomics is set to improve the accuracy, speed, reliability, cost-effectiveness and generalizability of pathology, especially in uro-oncology.",
keywords = "Artificial Intelligence, Carcinoma, Renal Cell/pathology, Deep Learning, Diagnosis, Computer-Assisted, Female, Humans, Kidney Neoplasms/pathology, Male, Neoplasm Grading, Pathology, Prostatic Neoplasms/pathology, Reproducibility of Results, Testicular Neoplasms/pathology, Urogenital Neoplasms/pathology, Urologic Neoplasms/pathology, Urology",
author = "Schuettfort, {Victor M} and Benjamin Pradere and Michael Rink and Eva Comperat and Shariat, {Shahrokh F}",
year = "2020",
month = nov,
doi = "10.1097/MOU.0000000000000813",
language = "English",
volume = "30",
pages = "823--831",
journal = "CURR OPIN UROL",
issn = "0963-0643",
publisher = "Lippincott Williams and Wilkins",
number = "6",

}

RIS

TY - JOUR

T1 - Pathomics in urology

AU - Schuettfort, Victor M

AU - Pradere, Benjamin

AU - Rink, Michael

AU - Comperat, Eva

AU - Shariat, Shahrokh F

PY - 2020/11

Y1 - 2020/11

N2 - PURPOSE OF REVIEW: Pathomics, the fusion of digitalized pathology and artificial intelligence, is currently changing the landscape of medical pathology and biologic disease classification. In this review, we give an overview of Pathomics and summarize its most relevant applications in urology.RECENT FINDINGS: There is a steady rise in the number of studies employing Pathomics, and especially deep learning, in urology. In prostate cancer, several algorithms have been developed for the automatic differentiation between benign and malignant lesions and to differentiate Gleason scores. Furthermore, several applications have been developed for the automatic cancer cell detection in urine and for tumor assessment in renal cancer. Despite the explosion in research, Pathomics is not fully ready yet for widespread clinical application.SUMMARY: In prostate cancer and other urologic pathologies, Pathomics is avidly being researched with commercial applications on the close horizon. Pathomics is set to improve the accuracy, speed, reliability, cost-effectiveness and generalizability of pathology, especially in uro-oncology.

AB - PURPOSE OF REVIEW: Pathomics, the fusion of digitalized pathology and artificial intelligence, is currently changing the landscape of medical pathology and biologic disease classification. In this review, we give an overview of Pathomics and summarize its most relevant applications in urology.RECENT FINDINGS: There is a steady rise in the number of studies employing Pathomics, and especially deep learning, in urology. In prostate cancer, several algorithms have been developed for the automatic differentiation between benign and malignant lesions and to differentiate Gleason scores. Furthermore, several applications have been developed for the automatic cancer cell detection in urine and for tumor assessment in renal cancer. Despite the explosion in research, Pathomics is not fully ready yet for widespread clinical application.SUMMARY: In prostate cancer and other urologic pathologies, Pathomics is avidly being researched with commercial applications on the close horizon. Pathomics is set to improve the accuracy, speed, reliability, cost-effectiveness and generalizability of pathology, especially in uro-oncology.

KW - Artificial Intelligence

KW - Carcinoma, Renal Cell/pathology

KW - Deep Learning

KW - Diagnosis, Computer-Assisted

KW - Female

KW - Humans

KW - Kidney Neoplasms/pathology

KW - Male

KW - Neoplasm Grading

KW - Pathology

KW - Prostatic Neoplasms/pathology

KW - Reproducibility of Results

KW - Testicular Neoplasms/pathology

KW - Urogenital Neoplasms/pathology

KW - Urologic Neoplasms/pathology

KW - Urology

U2 - 10.1097/MOU.0000000000000813

DO - 10.1097/MOU.0000000000000813

M3 - SCORING: Review article

C2 - 32881725

VL - 30

SP - 823

EP - 831

JO - CURR OPIN UROL

JF - CURR OPIN UROL

SN - 0963-0643

IS - 6

ER -