Assessing Perceptions of ML Explanations by Medical Oncologists

The objective of this proposal is to conduct a vignette-based survey among practicing oncology clinicians who treat non-small cell lung cancer to assess the trustworthiness of explainable predictions from a neurosymbolic AI vs. State-of-the-art post-hoc explanatory algorithms, using simulated patient data.

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Key information

Conditions

Oncology Neoplasms

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

University of Pennsylvania

Philadelphia, Pennsylvania, 19083, United States

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

"Medical oncologist" or "Hematologist/Oncologist" designation at Penn Treats lung cancer

Exclusion criteria

Non-medical oncologists No email address or physical address listed Does not treat lung cancer

Treatment and study plan

Once time de-identified Qualtrics survey

Other

Once time de-identified Qualtrics survey

Primary outcomes

Determine whether neurosymbolic AI explainability methods improve the trustworthiness of explanations from a prognostic model, relative to post-hoc explainers.

Time frame: 3 months

Oncologist will be invited to complete a vignette-based survey

Sponsors and collaborators

Lead sponsor

Abramson Cancer Center at Penn Medicine

Other

Registry information

Official study title

Survey of Medical Oncologists to Assess Trustworthiness of Various Approaches to AI Explainability for Prognostic Models

Important dates

Study start: 2024
Primary completion: 2028
Study completion: 2028
First posted: Nov 21, 2024
Registry last updated: Apr 6, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

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This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.

Enrolling by Invitation