2019
DOI: 10.1016/j.eururo.2019.08.032
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Augmented Bladder Tumor Detection Using Deep Learning

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Cited by 142 publications
(76 citation statements)
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“…The sensitivity and specificity per-frame of CystoNet was 90.9% and 98.6, respectively (detected 39 of 41 papillary and 3 of 3 flat bladder cancers). 11 Another DLS aims to predict the survival according to bladder cancer subtypes, using TCGA dataset of mRNA, miRNA, and methylation to infer two survival subtypes and apply it to any new individual sample. The high-risk survival subgroup had KRT6/14 overexpression and PI3K-Akt pathways.…”
Section: Discussion Precision Medicine and Genomic Markersmentioning
confidence: 99%
See 1 more Smart Citation
“…The sensitivity and specificity per-frame of CystoNet was 90.9% and 98.6, respectively (detected 39 of 41 papillary and 3 of 3 flat bladder cancers). 11 Another DLS aims to predict the survival according to bladder cancer subtypes, using TCGA dataset of mRNA, miRNA, and methylation to infer two survival subtypes and apply it to any new individual sample. The high-risk survival subgroup had KRT6/14 overexpression and PI3K-Akt pathways.…”
Section: Discussion Precision Medicine and Genomic Markersmentioning
confidence: 99%
“…8 All of these cutting-edge technological tools have been studied for the treatment of urolithiasis, urological cancer, hypospadias and have been able to successfully identify renal cell carcinoma, prostate carcinoma in surgical pathology and to discriminate tumors in white light cystoscopy. 7,[10][11][12][13][14][15][16] The aim of the present article is to present a detailed revision on precision medicine, including novel therapeutic targets, genomic markers and genomic stratification of urological patients, and the top-notch technological breakthroughs that could change our clinical practice.…”
Section: Introductionmentioning
confidence: 99%
“…B. bestehend aus Bildern oder kurzen Videosequenzen von TUR-B-Eingriffen), welche einen Abgleich von Struktur, Größe und Form von Blasentumoren per Software ermöglicht. Ein solches System kann während der WLZ in Echtzeit dem Untersucher Befunde rückmelden und so die Sensitivität und Spezifität erhöhen [16]. Erste Studien belegen die prinzipielle Umsetzbarkeit in der Praxis.…”
Section: Experimentelle Verfahren Zur Verbesserten Diagnostikunclassified
“…As to the superiority of feature learning, Deep Convolutional Neural Networks (DCNN) have been widely used in the computer aided diagnosis of bladder cancer, which includes bladder segmentation [3,11], bladder cancer detection [4,14] and staging [6,7]. For the cancer staging, existing DCNN-based methods directly classify the tumors into stages through extracting the non-semantic features from medical images.…”
Section: Introductionmentioning
confidence: 99%