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Related Concept Videos

Generalization, Discrimination, and Extinction01:24

Generalization, Discrimination, and Extinction

Generalization, discrimination, and extinction are key concepts in operant conditioning that influence how behaviors are learned and maintained.
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Goodness-of-Fit Test

The goodness-of-fit test is a type of hypothesis test which determines whether the data "fits" a particular distribution. For example, one may suspect that some anonymous data may fit a binomial distribution. A chi-square test (meaning the distribution for the hypothesis test is chi-square) can be used to determine if there is a fit. The null and alternative hypotheses may be written in sentences or stated as equations or inequalities. The test statistic for a goodness-of-fit test is given as...
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Survival Tree01:19

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Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
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Principle of Equivalence01:18

Principle of Equivalence

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Related Experiment Videos

Good for All, Not Good Enough for One: Reuse Dilemma in Federated Learning.

Ashkan Pirmani1,2,3, Yves Moreau1, Liesbet M Peeters2,3

  • 1ESAT, STADIUS, KU Leuven, Leuven, Belgium.

Studies in Health Technology and Informatics
|May 23, 2026
PubMed
Summary

Federated learning (FL) adoption in healthcare faces barriers. A case study revealed general-purpose frameworks are less effective than task-specific pipelines, highlighting the need for modular tools.

Keywords:
Federated LearningHealth InformaticsModularityResearch InfrastructureTechnology Adoption

Related Experiment Videos

Area of Science:

  • Health Informatics
  • Computer Science
  • Collaborative Research

Background:

  • Federated learning (FL) offers privacy-preserving collaboration in healthcare.
  • Real-world adoption of FL is hindered by infrastructural and organizational challenges.
  • General-purpose FL frameworks may not meet diverse research needs.

Purpose of the Study:

  • To analyze the barriers encountered during the development and implementation of a general-purpose FL framework in healthcare.
  • To propose an alternative approach using task-specific pipelines.
  • To identify key challenges hindering the reuse of FL tools in research.

Main Methods:

  • Retrospective analysis of a case study involving the development and subsequent abandonment of a general-purpose FL framework.
  • Comparison between a general-purpose FL framework and a task-specific pipeline.
  • Identification and categorization of barriers to FL tool reuse.

Main Results:

  • A general-purpose FL framework proved less effective than a task-specific pipeline.
  • Five core barriers to reuse were identified: workflow misalignment, governance constraints, and other unaddressed technical design issues.
  • The limitations of reuse in practical research settings were highlighted.

Conclusions:

  • Task-specific pipelines can be more effective than general-purpose frameworks in certain healthcare research contexts.
  • Modular and interoperable tools are needed to accommodate diverse research environments.
  • Realistic infrastructure planning that acknowledges reuse limitations is crucial for successful FL adoption.