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Towards fair decentralized benchmarking of healthcare AI algorithms with the Federated Tumor Segmentation (FeTS) challenge

Federated learning (FL) algorithms have emerged as a promising solution to train models for healthcare imaging across institutions while preserving privacy. Here, the authors describe the Federated Tumor Segmentation (FeTS) challenge for the decentralised benchmarking of FL algorithms and evaluation of Healthcare AI algorithm generalizability in real-world cancer imaging datasets.

Maximilian Zenk
Ujjwal Baid
Spyridon Bakas
ResearchOpen Access08 Jul 2025
Nature Communications

Volume: 16, P: 1-20
Federated learning enables big data for rare cancer boundary detection

Federated ML (FL) provides an alternative to train accurate and generalizable ML models, by only sharing numerical model updates. Here, the authors present the largest FL study to-date to generate an automatic tumor boundary detector for glioblastoma.

Sarthak Pati
Ujjwal Baid
Spyridon Bakas
ResearchOpen Access05 Dec 2022
Nature Communications

Volume: 13, P: 1-17
Prospective study to define the clinical utility and benefit of Decipher testing in men following prostatectomy

Joseph Marascio
Daniel E. Spratt
Robert B. Den
ResearchOpen Access12 Nov 2019
Prostate Cancer and Prostatic Diseases

Volume: 23, P: 295-302
Evolution of advanced technologies in prostate cancer radiotherapy

In this Review, the authors discuss the novel, technologically advanced radiotherapy modalities for the primary treatment of men with prostate cancer. Advancements in image-guided and intensity-modulated techniques are discussed, focusing on how these modalities contributed to the development of high-dose-rate brachytherapy, stereotactic body radiotherapy and particle beam therapy.

Nicholas G. Zaorsky
Amy S. Harrison
Robert B. Den
Reviews10 Sept 2013
Nature Reviews Urology

Volume: 10, P: 565-579
Author Correction: Federated learning enables big data for rare cancer boundary detection

Sarthak Pati
Ujjwal Baid
Spyridon Bakas
Amendments and CorrectionsOpen Access26 Jan 2023
Nature Communications

Volume: 14, P: 1-2
E-mail and oncology: a survey of radiation oncology patients and their attitudes to a new generation of health communication

C Katzen
M J Solan
A P Dicker
Research26 Apr 2005
Prostate Cancer and Prostatic Diseases

Volume: 8, P: 189-193
Effects of androgen suppression and radiation on prostate cancer suggest a role for angiogenesis blockade

W A Woodward
P Wachsberger
A P Dicker
Reviews11 Jan 2005
Prostate Cancer and Prostatic Diseases

Volume: 8, P: 127-132

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Towards fair decentralized benchmarking of healthcare AI algorithms with the Federated Tumor Segmentation (FeTS) challenge

Federated learning enables big data for rare cancer boundary detection

Prospective study to define the clinical utility and benefit of Decipher testing in men following prostatectomy

Evolution of advanced technologies in prostate cancer radiotherapy

Author Correction: Federated learning enables big data for rare cancer boundary detection

E-mail and oncology: a survey of radiation oncology patients and their attitudes to a new generation of health communication

Effects of androgen suppression and radiation on prostate cancer suggest a role for angiogenesis blockade

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