Subgroup Discovery for Treatment Optimization

6 pages•Published: June 4, 2018

Abstract

Modern medicine aspire to improve the effectiveness of treatment for some diseases through, so called, personalized medicine. However, totally personalized medicine or personalized treatment of even one disease is a very ambitious goal. Subgroup analysis of patients is a preliminary step to the total personalization. Several completely different views on the principles and usefulness of subgroup analysis for treatment personalization exist. This paper is limited to data-driven subgroup discovery, when collected data analyzed for significant treatment-biomarker interactions in post-hoc manner, and presents a brief overview of key methods for this type of subgroup analysis.

Keyphrases: personalized medicine, subgroup analysis, subgroup discovery

In: Oleg S. Pianykh, Alexey Neznanov, Sergei Kuznetsov, Jaume Baixeries and Svetla Boytcheva (editors). WDAM-2017. Workshop on Data Analysis in Medicine, vol 6, pages 48-53.

Links:	https://easychair.org/publications/paper/8sm4
	https://doi.org/10.29007/hztj

BibTeX entry

@inproceedings{WDAM-2017:Subgroup_Discovery_Treatment_Optimization,
  author    = {Natalia Korepanova},
  title     = {Subgroup Discovery for Treatment Optimization},
  booktitle = {WDAM-2017. Workshop on Data Analysis in Medicine},
  editor    = {Oleg S. Pianykh and Alexey Neznanov and Sergei Kuznetsov and Jaume Baixeries and Svetla Boytcheva},
  series    = {Kalpa Publications in Computing},
  volume    = {6},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2515-1762},
  url       = {/publications/paper/8sm4},
  doi       = {10.29007/hztj},
  pages     = {48-53},
  year      = {2018}}

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