Biased by Design: How Digital Health in Neurology Fails—and Can Serve—Marginalized Patients (P2-14.006)

Q: What does this research mean for the field?

AI and digital health technologies in neurology currently exhibit biases that fail marginalized patients, necessitating an equity-centered framework for inclusive design. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

Victor Ekuta

doi:10.1212/wnl.0000000000215274

June 9, 2026Neurology

Biased by Design: How Digital Health in Neurology Fails—and Can Serve—Marginalized Patients (P2-14.006)

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Key Points

This study aims to explore the emergence of bias in AI and digital health technologies in neurology and offers a framework for inclusive design.
Analyzed how biases are created in digital health technologies used in neurology.
Proposed an equity-centered framework for inclusive innovation in digital health.
Identified key areas where digital health technologies may fail marginalized populations.
Proposed actionable guidelines for designing more equitable digital health solutions.

Implication

Examines bias in AI technologies in neurology, suggesting frameworks for equitable design and innovation.

Abstract

To examine how bias emerges within AI and digital health technologies across neurology and to propose an equity-centered framework to guide inclusive design and innovation.

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Cite This Study

Victor Ekuta (2026) studied this question.

synapsesocial.com/papers/6a2cf34dfaef96ed7f055d3c https://doi.org/10.1212/wnl.0000000000215274

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Biased by Design: How Digital Health in Neurology Fails—and Can Serve—Marginalized Patients (P2-14.006)

Key Points

Implication

Abstract

Discussion

Cite This Study

Biased by Design: How Digital Health in Neurology Fails—and Can Serve—Marginalized Patients (P2-14.006)

Key Points

Implication

Abstract

Discussion

Cite This Study

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