Explainable AI for Clinical Outcome Prediction: A Survey of Clinician Perceptions and Preferences

• URL: http://arxiv.org/abs/2502.20478v1
• Date: Thu, 27 Feb 2025 19:30:20 GMT
• Title: Explainable AI for Clinical Outcome Prediction: A Survey of Clinician Perceptions and Preferences
• Authors: Jun Hou, Lucy Lu Wang,
• Abstract summary: Explainable AI (XAI) techniques are necessary to help clinicians make sense of AI predictions and integrate predictions into their decision-making workflow.<n>We implement four XAI techniques on an outcome prediction model that uses ICU admission notes to predict a patient's likelihood of experiencing in-hospital mortality.<n>We conduct a survey study of 32 practicing clinicians, collecting their feedback and preferences on the four techniques.<n>We synthesize our findings into a set of recommendations describing when each of the XAI techniques may be more appropriate, their potential limitations, as well as recommendations for improvement.
• Score: 11.236899989769574
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Explainable AI (XAI) techniques are necessary to help clinicians make sense of AI predictions and integrate predictions into their decision-making workflow. In this work, we conduct a survey study to understand clinician preference among different XAI techniques when they are used to interpret model predictions over text-based EHR data. We implement four XAI techniques (LIME, Attention-based span highlights, exemplar patient retrieval, and free-text rationales generated by LLMs) on an outcome prediction model that uses ICU admission notes to predict a patient's likelihood of experiencing in-hospital mortality. Using these XAI implementations, we design and conduct a survey study of 32 practicing clinicians, collecting their feedback and preferences on the four techniques. We synthesize our findings into a set of recommendations describing when each of the XAI techniques may be more appropriate, their potential limitations, as well as recommendations for improvement.

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