Real-time prediction of cardiovascular diseases using reservoir-computing and fusion with electronic medical record

Sudarsan Sadasivuni, Vasundhara Damodaran, Imon Banerjee, Arindam Sanyal

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

Abstract

Cardiovascular diseases (CVDs) are a leading cause of death in USA and globally, but many people suffering from CVDs are asymptomatic in the early stages leading to reduced awareness, and less chances of managing the disease. This work presents a potential solution for at-home monitoring by leveraging predictive power of artificial intelligence (AI) for developing a fusion framework that combines patient electrocardiogram (ECG) and electronic medical record (EMR) for predicting risk of CVDs at an early stage. To improve energy-efficiency of wearable ECG sensor, in-sensor analog reservoir-computing is proposed that precludes need for front-end digitization and transmission of raw sensor data. The fusion framework predicts ischemic heart disease (I20-I25 ICD codes) with area under the receiver operating characteristic (AUROC) of 0.91, and other heart diseases (I30-I52 ICD codes) with AUROC of 0.95 which is better than state-of-the-art while not requiring laboratory test results.

Original languageEnglish (US)
Title of host publicationProceeding - IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages58-61
Number of pages4
ISBN (Electronic)9781665409964
DOIs
StatePublished - 2022
Event4th IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2022 - Incheon, Korea, Republic of
Duration: Jun 13 2022Jun 15 2022

Publication series

NameProceeding - IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2022

Conference

Conference4th IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2022
Country/TerritoryKorea, Republic of
CityIncheon
Period6/13/226/15/22

Keywords

  • artificial intelligence
  • artificial neural network
  • cardiovascular disease
  • data fusion
  • in-memory computing
  • reservoir-computer

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Human-Computer Interaction
  • Electrical and Electronic Engineering

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