Biomedical Applications: Diagnostic and Prognostic

Ilia Nouretdinov, Tony Bellotti, Alexander Gammerman

Research output: Chapter in Book/Conference proceedingBook Chapterpeer-review

Abstract

There are several important advantages in applying conformal predictors (CP) in medical diagnostics. First of all, CPs provide valid measures of confidence in the diagnosis; this is often a crucial advantage for medical decision-making since it allows the estimation of risk of an erroneous clinical decision for an individual patient. Moreover, the risk of clinical errors may be controlled by an acceptable level of confidence for a given clinical decision and therefore the risk of misdiagnosis is known. Another feature that makes CPs an attractive method in medical applications is that they are region predictors. This means that if we do not have enough information to make a definitive diagnosis, the method would allow us to make a number of possible (multiple) diagnoses and a patient may require further tests to narrow down the available options.

Original languageEnglish
Title of host publicationConformal Prediction for Reliable Machine Learning
Subtitle of host publicationTheory, Adaptations and Applications
PublisherElsevier Inc.
Pages217-230
Number of pages14
ISBN (Print)9780123985378
DOIs
Publication statusPublished - Apr 2014
Externally publishedYes

Keywords

  • Biomedical Applications
  • Diagnostics
  • Microarrays
  • Nonconformity Measures
  • Prognostics
  • Proteomics

ASJC Scopus subject areas

  • Computer Science (all)

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