Risk-O-Meter: An intelligent clinical risk calculator

Kiyana Zolfaghar, Jayshree Agarwal, Deepthi Sistla, Si Chi Chin, Senjuti Basu Roy, Nele Verbiest

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

We present a system called Risk-O-Meter to predict and analyze clinical risk via data imputation, visualization, predictive modeling, and association rule exploration. Clinical risk calculators provide information about a person's chance of having a disease or encountering a clinical event. Such tools could be highly useful to educate patients to understand and monitor their health conditions. Unlike existing risk calculators that are primarily designed for domain experts, Risk- O-Meter is useful to patients who are unfamiliar with medical terminologies, or providers who have limited information about a patient. Risk-O-Meter is designed in a way such that it is exible enough to accept limited or incomplete data in- puts, and still manages to predict the clinical risk efficiently and effiectively. Current version of Risk-O-Meter evaluates 30-day risk of hospital readmission. However, the proposed system framework is applicable to general clinical risk pre- dictions. In this demonstration paper, we describe different components of Risk-O-Meter and the intelligent algorithms associated with each of these components to evaluate risk of readmission using incomplete patient data inputs.

Original languageEnglish (US)
Title of host publicationKDD 2013 - 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
EditorsRajesh Parekh, Jingrui He, Dhillon S. Inderjit, Paul Bradley, Yehuda Koren, Rayid Ghani, Ted E. Senator, Robert L. Grossman, Ramasamy Uthurusamy
PublisherAssociation for Computing Machinery
Pages1518-1521
Number of pages4
ISBN (Electronic)9781450321747
DOIs
StatePublished - Aug 11 2013
Externally publishedYes
Event19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013 - Chicago, United States
Duration: Aug 11 2013Aug 14 2013

Publication series

NameProceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
VolumePart F128815

Other

Other19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013
Country/TerritoryUnited States
CityChicago
Period8/11/138/14/13

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems

Keywords

  • Association rule mining
  • Clinical risk calculator
  • Clustering
  • Risk of hospital readmission predication

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