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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
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Does AI explainability affect physicians' intention to use AI?

Chung-Feng Liu1, Zhih-Cherng Chen2, Szu-Chen Kuo3

  • 1Department of Medical Research, Chi Mei Medical Center, No. 901, Zhonghua Rd., Yongkang Dist., Tainan City 710402, Taiwan.

International Journal of Medical Informatics
|October 13, 2022
PubMed
Summary
This summary is machine-generated.

Physicians show high intention to use Artificial Intelligence (AI) in healthcare. Explainable AI (XAI) significantly impacts technology trust and perceived value, crucial for AI adoption in clinical settings.

Keywords:
AI explainability (XAI)Artificial intelligence (AI)Behavioral intentionPerceived valuePhysicianTechnology trust

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Area of Science:

  • Healthcare Technology
  • Medical Informatics
  • Artificial Intelligence

Background:

  • AI adoption in hospitals is hindered by unclear explainability (XAI).
  • Physicians' trust and perceived value are key factors in AI adoption.
  • Limited understanding of XAI's role in physician AI adoption.

Purpose of the Study:

  • To develop and validate a conceptual model for physician AI adoption intention.
  • To investigate the role of explainable AI (XAI) as an antecedent to technology trust (TT) and perceived value (PV).
  • To explore the relationships between XAI, TT, PV, and behavioral intention (BI) to use AI.

Main Methods:

  • Questionnaire survey administered to physicians in three Taiwanese hospitals.
  • Structural Equation Modeling (SEM) used for model validation and hypothesis testing.
  • Data collected from 295 valid physician responses.

Main Results:

  • Physicians reported a high intention to use AI.
  • XAI significantly influenced AI technology trust (TT) and perceived value (PV).
  • TT and PV significantly impacted physicians' behavioral intention (BI) to use AI.

Conclusions:

  • The conceptual model provides guidelines for understanding physician AI adoption drivers.
  • XAI is crucial for building trust and perceived value in medical AI.
  • Findings offer insights into AI-human interaction in healthcare.