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N/ARecruiting

Safe and Explainable AI

Sponsored by Abramson Cancer Center at Penn Medicine

About this study

While current AI technology is suitable for automating some repetitive clinical tasks, technical challenges remain in solving critical and gainful problems in the domains of patient and disease management. The proposed research seeks to address issues in medical AI, such as integrating medical knowledge effectively, making AI recommendations explainable to clinicians, and establishing safety guarantees.

Where this study is enrolling

  • Hospital of the University of Pennsylvania

    Philadelphia, Pennsylvania

    I'm interested
Who can participate

Inclusion criteria

  • ✓Cardiology 18 years of age and older, admitted to any of the Penn Medicine hospitals from 2017 to the present. Sepsis 18 years of age at the time of presentation to an emergency department or admission to any Penn Medicine hospital from July 1, 2017, onward will be eligible as this represents the population at risk for acquiring sepsis Oncology 18 years of age and older with a diagnosis of invasive breast cancer (Stage 1-4) in the Penn Cancer registry

Exclusion criteria

  • ✕All prediction models will exclude patients under the age of 18 from their patient data sets.
  • ✕Cardiology Patients whose primary admission diagnosis was cardiac arrest Sepsis Those with pre-existing limitations on life-sustaining therapy will be excluded because their eligibility for sepsis definitions, care received, and outcomes, may be significantly and variably affected by pre-existing limitations on care. Oncology There are no other exclusions.

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Completing a questionnaire on Clinably does not enroll you in a clinical trial or confirm your eligibility. Only the research team can determine whether you qualify to participate. These results are based on the information you provide and are intended to help you start a conversation with the research team.

Trial data sourced from ClinicalTrials.gov.