The number of inherited heart disease (IHD) studies using artificial intelligence (AI) has increased rapidly over the last years. In this scoping review, we aimed to present an overview of the current literature available on the applicability of AI within the field of IHD. The literature search resulted in eighteen articles in which an AI model was trained and tested, mostly for diagnostic and predictive purposes. The areas under the receiver operating characteristic curves ranged from 0.78-0.96, but varied between IHD types, used methods and outcome measures. Only three out of eighteen did perform validation on an external dataset and most studies did not use explainable deep learning models. To be able to integrate AI as a tool to aid physicians in their diagnoses and clinical decisions within the IHD field, generalizability has to be better evaluated and explainability of DL models has to be increased.
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http://dx.doi.org/10.1016/j.tcm.2022.01.011 | DOI Listing |
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