Machine learning in renal cell carcinoma research: the promise and pitfalls of ‘renal‐izing’ the potential of artificial intelligence-Reference-Cited by-同舟云学术

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Machine learning in renal cell carcinoma research: the promise and pitfalls of ‘renal‐izing’ the potential of artificial intelligence

Published:2023-04-10 Issue:2 Volume:132 Page:231-232
ISSN:1464-4096
Container-title:BJU International
language:en
Short-container-title:BJU International

Author:

Khene Zine‐Eddine¹²^ORCID,Kutikov Alexander³,Campi Riccardo⁴⁵⁶^ORCID,

Affiliation:

1. Department of Urology Rennes University Hospital Rennes France

2. Signal and Image Processing Laboratory (LTSI) University of Rennes INSERM Rennes France

3. Division of Urologic Oncology, Department of Surgical Oncology Fox Chase Cancer Center Philadelphia PA USA

4. Unit of Urological Minimally Invasive, Robotic Surgery and Kidney Transplantation, Careggi Hospital University of Florence Florence Italy

5. Department of Experimental and Clinical Medicine University of Florence Florence Italy

6. European Association of Urology (EAU) Young Academic Urologists (YAU) Renal Cancer Working Group Arnhem The Netherlands

Publisher

Wiley

Subject

Urology

Reference13 articles.

1. Kidney cancer management 3.0: can artificial intelligence make us better?

2. Application of Machine Learning Models to Predict Recurrence After Surgical Resection of Nonmetastatic Renal Cell Carcinoma

3. Machine‐learning approach for prediction of pT3a upstaging and outcomes of localized renal cell carcinoma (UroCCR‐15)

4. Computer-Generated R.E.N.A.L. Nephrometry Scores Yield Comparable Predictive Results to Those of Human-Expert Scores in Predicting Oncologic and Perioperative Outcomes

5. How to Read Articles That Use Machine Learning

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Reply to: machine learning in renal cell carcinoma research: promise and pitfalls of ‘renal‐izing’ the potential of artificial intelligence;BJU International;2023-07-28

2. Artificial Intelligence in Renal Cell Carcinoma Histopathology: Current Applications and Future Perspectives;Diagnostics;2023-07-06

3. The BJUI Editorial Team's view on artificial intelligence and machine learning;BJU International;2023-04-27

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