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February 12, 2026Open Access

[Medical ML] Explainable AI (XAI) for Clinical Trust: Bridging the Black Box Gap

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Key Points

The aim is to explore how explainable AI can improve trust in clinical settings using machine learning.
Analyzed current machine learning techniques in healthcare.
Examined challenges related to the black box nature of AI models.
Evaluated the effectiveness of explainable AI frameworks in medical diagnosis.
Identified key trust barriers in AI applications in healthcare.
Proposed strategies for implementing explainable AI solutions in clinical practice.

Implication

Part of Medical ML shows the potential of explainable AI to enhance clinical trust in healthcare, suggesting a bridge over the black box gap.

Abstract

Part of the Medical ML Research Series: Machine Learning for Medical Diagnosis in Ukrainian Healthcare. Published on Stabilarity Research Hub.

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Cite This Study

Oleh Ivchenko (2026) studied this question.

synapsesocial.com/papers/699011812ccff479cfe583ff https://doi.org/10.5281/zenodo.18615996

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