The Mendelian Phenotype Search Engine (MPSE), a clinical decision support tool using Natural Language Processing and Machine Learning, helped neonatologists expedite decisions to whole genome sequencing (WGS) to diagnose patients in the Neonatal Intensive Care Unit. After the MPSE was introduced, utilization of WGS increased, time to ordering WGS decreased, and WGS diagnostic yield increased.

C Tackaberry is a director and employee of Clinithink and also a shareholder. No other competing interests from any author to disclose.

This study was funded by the Conrad Prebys Foundation. R.R. is supported by NCATS grant number K12TR004410.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

WCG IRB gave approval for this work

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

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I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

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I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

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De-identified data utilized in this paper is attached as supplementary material; including time from admission to nomination, MPSE score, WGS results for enrolled patients, and reasons for decline for patients who did not enroll.