Assessing Perceptions of ML Explanations by Medical Oncologists

Not Applicable

• Conditions: Oncology

• Registration Number: NCT06699615
• Lead Sponsor: Abramson Cancer Center at Penn Medicine

Brief Summary

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.

Detailed Description

Not available

Study Timeline

• Study First Submitted: 2024-11-19
• Study First Submitted QC: 2024-11-19
• Study First Posted: 2024-11-21
• Study Start: 2024-12-02
• Status Verified: 2025-01
• Last Update Submitted: 2025-01-29
• Last Update Posted: 2025-01-31
• Primary Completion: 2025-04-15
• Study Completion: 2025-04-15

Recruitment & Eligibility

• Status: ENROLLING_BY_INVITATION
• Sex: All
• Target Recruitment: 50

Inclusion Criteria

Not provided

Exclusion Criteria

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

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: SINGLE_GROUP

Primary Outcome Measures

Name	Time	Method
Determine whether neurosymbolic AI explainability methods improve the trustworthiness of explanations from a prognostic model, relative to post-hoc explainers.	3 months	Oncologist will be invited to complete a vignette-based survey

Trial Locations

Locations (1)

University of Pennsylvania; 🇺🇸 Philadelphia, Pennsylvania, United States