Artificial Intelligence-enabled Electrocardiogram and Phonocardiogram to improve detection of Congenital Heart Disease

Overview

About this study

The purpose of the study is to develop and validate artificial Intelligence (AI) enabled sceening tools for the early detection of congenital heart disease (CHD) in newborns. This involves developing algorithms based electrocardiogram (ECG) and phonocardiogram data, both retrospective and prospectively. The study aims to improve upon current screening methods, such as pulse-oximetry, which have limitations in detecting both critical and non-critical CHD. By leveraging AI technology, the study seeks to enhance the accuracy and accessibility of CHD screening, potentially leading to better outcomes for affected newborns. 

Participation eligibility

Participant eligibility includes age, gender, type and stage of disease, and previous treatments or health concerns. Guidelines differ from study to study, and identify who can or cannot participate. There is no guarantee that every individual who qualifies and wants to participate in a trial will be enrolled. Contact the study team to discuss study eligibility and potential participation.

Inclusion Criteria:

  • Children < 3 months of age born at or admitted at Mayo Clinic Hospitals, Rochester, MN

Exclusion Criteria: 

  • Parental unwillingness or inability to provide informed consent.
  • Inability of the child to remain still to obtain the research ECG

Note: Other protocol defined Inclusion/Exclusion Criteria may apply.

Eligibility last updated 2/27/2024. Questions regarding updates should be directed to the study team contact

Participating Mayo Clinic locations

Study statuses change often. Please contact the study team for the most up-to-date information regarding possible participation.

Mayo Clinic Location Status Contact

Rochester, Minn.

Mayo Clinic principal investigator

Malini Madhavan, M.B.B.S.

Open for enrollment

Contact information:

Heart Failure Research Team

(507) 422-6190

More information

Publications

Publications are currently not available
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CLS-20577627

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