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1
AI models analyzing speech can effectively detect cognitive decline, achieving performance comparable to traditional clinical assessments.
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2
The 'black box' nature of many AI models hinders their clinical adoption, as healthcare professionals require transparent decision-making processes.
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3
Explainable AI (XAI) techniques, such as SHAP and LIME, enhance the interpretability of AI models used for detecting cognitive decline through speech.
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4
Speech changes, including reduced lexical diversity and altered speech fluency, serve as early indicators of cognitive decline, suitable for AI analysis.
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5
Despite advancements, significant gaps remain in stakeholder engagement, real-world validation, and standardized evaluation frameworks for XAI in healthcare.
