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Article Dans Une Revue European Urology Oncology Année : 2023

Clinical Application of Digital and Computational Pathology in Renal Cell Carcinoma: A Systematic Review

Pierre Bigot
Renaud de Crevoisier
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Morgan Roupret

Résumé

Computational pathology is a new interdisciplinary field that combines traditional with modern technologies such as digital imaging and machine learning to better understand the diagnosis, prognosis, natural history of many diseases.To provide an overview computational its current potential applications in renal cell carcinoma (RCC).A systematic review English-language literature was conducted using PubMed, Web Science, Scopus databases December 2022 according Preferred Reporting Items for Systematic Reviews Meta-Analyses guidelines (PROSPERO ID: CRD42023389282). Risk bias assessed Prediction Model Study Bias Assessment Tool.In total, 20 articles were included review. All studies used retrospective design, all techniques implemented retrospectively. The classified their primary objective: detection, tumor characterization, patient outcome. Regarding transition clinical practice, several showed promising potential. However, none presented comprehensive assessment utility implementation. Notably, there substantial heterogeneity both strategies model building performance metrics reported.This highlights vast classification, oncological outcomes RCC. Preliminary work this has yielded results. these models have not yet reached stage where they can be integrated into routine practice.Computational artificial intelligence improve diagnosis disease identify prognostic factors biomarkers. number exploring kidney cancer rapidly increasing. despite surge research activity, ready widespread use.
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Dates et versions

hal-04301561 , version 1 (23-11-2023)

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Zine-Eddine Khene, Solène-Florence Kammerer-Jacquet, Pierre Bigot, Noémie Rabilloud, Laurence Albiges, et al.. Clinical Application of Digital and Computational Pathology in Renal Cell Carcinoma: A Systematic Review. European Urology Oncology, 2023, European Urology Oncology, ⟨10.1016/j.euo.2023.10.018⟩. ⟨hal-04301561⟩
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