PROSurvival: A Technical Case Report on Creating and Publishing a Dataset for Federated Learning on Survival Prediction of Prostate Cancer Patients

Authors

Tom Bisson (ORCID: https://orcid.org/0000-0002-7743-0792)
Marco Eichelberg (ORCID: https://orcid.org/0000-0002-8590-3318)
Tim‐Rasmus Kiehl (ORCID: https://orcid.org/0000-0003-0616-7082)
Timo Wolters
Norman Zerbe (ORCID: https://orcid.org/0000-0002-0314-3037)
Tingyan Xu
Nadine Flinner (ORCID: https://orcid.org/0000-0002-8565-6492)
Johannes Lotz (ORCID: https://orcid.org/0000-0003-3387-2596)

Institutions

Goethe University Frankfurt (DE)
Oldenburger Institut für Informatik (DE)
Humboldt-Universität zu Berlin (DE)
Fraunhofer Institute for Digital Medicine (DE)
Freie Universität Berlin (DE)
Charité - Universitätsmedizin Berlin (DE)

Publication Details

Journal: Studies in health technology and informatics
Published: 2024-11-22
DOI: https://doi.org/10.3233/shti241096
Primary Topic: Prostate Cancer Diagnosis and Treatment
Type: article
Field-Weighted Citation Impact: 0.00

Controls

|||

ALL TIME

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

article

PROSurvival: A Technical Case Report on Creating and Publishing a Dataset for Federated Learning on Survival Prediction of Prostate Cancer Patients

Tom Bisson, Marco Eichelberg, Tim‐Rasmus Kiehl, Timo Wolters et al.

Nov 22, 2024

Studies in health technology and informatics

Prostate Cancer Diagnosis and Treatment

article

PROSurvival: A Technical Case Report on Creating and Publishing a Dataset for Federated Learning on Survival Prediction of Prostate Cancer Patients

Tom Bisson, Marco Eichelberg, Tim‐Rasmus Kiehl, Timo Wolters, Norman Zerbe, Tingyan Xu, Nadine Flinner, Johannes Lotz

November 22, 2024article en

Abstract

No abstract available for this paper.

Studies in health technology and informaticsVol. 321

Goethe University Frankfurt (DE), Oldenburger Institut für Informatik (DE), Humboldt-Universität zu Berlin (DE), Fraunhofer Institute for Digital Medicine (DE), Freie Universität Berlin (DE), Charité - Universitätsmedizin Berlin (DE)

Openalex Percentile: Top 32%

Prostate Cancer Diagnosis and Treatment

DOI Open Access PDF OpenAlex

AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

PROSurvival: A Technical Case Report on Creating and Publishing a Dataset for Federated Learning on Survival Prediction of Prostate Cancer Patients — Tom Bisson, Marco Eichelberg, et al. · Studies in health technology and informatics (2024) | TGRS Research Map | TGRS