PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
April 3, 20260 citationsOpen Access

A Federated Artificial Intelligence Framework for Optimizing Pancreatic Cancer Treatment – a Technical Case Report

AHAnne-Christin HauschildAAAmirreza AleyasinNBNils Beyer

Key Points

  • The aim is to explore how federated learning can enhance the treatment of pancreatic cancer by optimizing data use without central collection.
  • Utilized a federated artificial intelligence framework
  • Focused on patient data optimization
  • Analyzed predictive performance metrics
  • Improved predictive performance observed with federated learning
  • Enhanced data quality without central data gathering
  • Demonstrated feasibility of using federated architectures in clinical settings

Abstract

Introduction: Ideally, centrally collecting and analyzing patient data with appropriate consent would provide optimal data quality and predictive performance; however, this approach is often not feasible in practice. Federated Learning (FL) or Federated Artificial Intelligence architectures have shown for full text, please go to the a.m. URL

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Hauschild et al. (2026) studied this question.

synapsesocial.com/papers/69cf5c925a333a821460a2dbhttps://doi.org/10.3205/25gmds198
Ask AI
Helpful
Bookmark
Share
View Full Paper