-
Something wrong with this record ?
Pathomics in urology
VM. Schuettfort, B. Pradere, M. Rink, E. Comperat, SF. Shariat
Language English Country United States
Document type Journal Article, Research Support, Non-U.S. Gov't, Review
- MeSH
- Deep Learning MeSH
- Diagnosis, Computer-Assisted MeSH
- Carcinoma, Renal Cell pathology MeSH
- Humans MeSH
- Kidney Neoplasms pathology MeSH
- Prostatic Neoplasms pathology MeSH
- Pathology * MeSH
- Reproducibility of Results MeSH
- Neoplasm Grading MeSH
- Testicular Neoplasms pathology MeSH
- Artificial Intelligence * MeSH
- Urogenital Neoplasms pathology MeSH
- Urologic Neoplasms pathology MeSH
- Urology * MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Review MeSH
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.
Department of Urology 2nd Faculty of Medicine Charles University Prague Czech Republic
Department of Urology University Hospital of Tours Tours
Department of Urology University Medical Center Hamburg Eppendorf Hamburg Germany
Department of Urology University of Texas Southwestern Dallas Texas USA
Department of Urology Weill Cornell Medical College New York New York
European Association of Urology Research Foundation Arnhem Netherlands
Institute for Urology and Reproductive Health Sechenov University Moscow Russia
Karl Landsteiner Institute of Urology and Andrology Vienna Austria
References provided by Crossref.org
- 000
- 00000naa a2200000 a 4500
- 001
- bmc21019870
- 003
- CZ-PrNML
- 005
- 20210830101453.0
- 007
- ta
- 008
- 210728s2020 xxu f 000 0|eng||
- 009
- AR
- 024 7_
- $a 10.1097/MOU.0000000000000813 $2 doi
- 035 __
- $a (PubMed)32881725
- 040 __
- $a ABA008 $b cze $d ABA008 $e AACR2
- 041 0_
- $a eng
- 044 __
- $a xxu
- 100 1_
- $a Schuettfort, Victor M $u Department of Urology, Comprehensive Cancer Center, Vienna General Hospital, Medical University of Vienna, Vienna, Austria $u Department of Urology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- 245 10
- $a Pathomics in urology / $c VM. Schuettfort, B. Pradere, M. Rink, E. Comperat, SF. Shariat
- 520 9_
- $a 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.
- 650 12
- $a umělá inteligence $7 D001185
- 650 _2
- $a karcinom z renálních buněk $x patologie $7 D002292
- 650 _2
- $a deep learning $7 D000077321
- 650 _2
- $a diagnóza počítačová $7 D003936
- 650 _2
- $a ženské pohlaví $7 D005260
- 650 _2
- $a lidé $7 D006801
- 650 _2
- $a nádory ledvin $x patologie $7 D007680
- 650 _2
- $a mužské pohlaví $7 D008297
- 650 _2
- $a stupeň nádoru $7 D060787
- 650 12
- $a patologie $7 D010336
- 650 _2
- $a nádory prostaty $x patologie $7 D011471
- 650 _2
- $a reprodukovatelnost výsledků $7 D015203
- 650 _2
- $a testikulární nádory $x patologie $7 D013736
- 650 _2
- $a urogenitální nádory $x patologie $7 D014565
- 650 _2
- $a urologické nádory $x patologie $7 D014571
- 650 12
- $a urologie $7 D014572
- 655 _2
- $a časopisecké články $7 D016428
- 655 _2
- $a práce podpořená grantem $7 D013485
- 655 _2
- $a přehledy $7 D016454
- 700 1_
- $a Pradere, Benjamin $u Department of Urology, Comprehensive Cancer Center, Vienna General Hospital, Medical University of Vienna, Vienna, Austria $u Department of Urology, University Hospital of Tours, Tours
- 700 1_
- $a Rink, Michael $u Department of Urology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- 700 1_
- $a Comperat, Eva $u Department of Pathology, Sorbonne University, Assistance Publique-Hôpitaux de Paris, Hopital Tenon, Paris, France
- 700 1_
- $a Shariat, Shahrokh F $u Department of Urology, Comprehensive Cancer Center, Vienna General Hospital, Medical University of Vienna, Vienna, Austria $u Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia $u Department of Urology, Weill Cornell Medical College, New York, New York $u Department of Urology, University of Texas Southwestern, Dallas, Texas, USA $u Department of Urology, Second Faculty of Medicine, Charles University, Prague, Czech Republic $u Karl Landsteiner Institute of Urology and Andrology, Vienna, Austria $u European Association of Urology Research Foundation, Arnhem, Netherlands
- 773 0_
- $w MED00001296 $t Current opinion in urology $x 1473-6586 $g Roč. 30, č. 6 (2020), s. 823-831
- 856 41
- $u https://pubmed.ncbi.nlm.nih.gov/32881725 $y Pubmed
- 910 __
- $a ABA008 $b sig $c sign $y p $z 0
- 990 __
- $a 20210728 $b ABA008
- 991 __
- $a 20210830101453 $b ABA008
- 999 __
- $a ok $b bmc $g 1690635 $s 1140316
- BAS __
- $a 3
- BAS __
- $a PreBMC
- BMC __
- $a 2020 $b 30 $c 6 $d 823-831 $e - $i 1473-6586 $m Current opinion in urology $n Curr Opin Urol $x MED00001296
- LZP __
- $a Pubmed-20210728