Equitable AI Addressing Expanding Artificial Intelligence And Machine Learning To Improve Recovery From Acute Illness: A Patient-Focused Collaborative Hospital Repository Uniting Standards

Overview

About this study

The purpose of this study is to integrate newly developed and existing AI/ML tools to create an ethically sourced, diverse, accessible, patient-focused, and AI-ready CHoRUS dataset that meets our grand challenge to improve recovery from acute illnesses. Also, to develop and execute processes to conduct prospective collection, integration, annotation, and release of linked high-resolution physiological data and electronic health records of adult and pediatric Critical Care patients from 14 US health systems.

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: 

  • N/A - deidentified data. 

Exclusion Criteria: 

  • N/A - deidentified data. 

Eligibility last updated 6/24/22. 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

Rochester, Minn.

Mayo Clinic principal investigator

Vitaly Herasevich, M.D., Ph.D.

Contact us for the latest status

More information

Publications

Publications are currently not available
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CLS-20598440

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