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Updated: Jan 14, 2026

High-definition Transcranial Direct Current Stimulation over Right Dorsolateral Prefrontal Cortex to Enhance Metacognitive Sensitivity
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Published on: September 26, 2025

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Artificial Intelligence and Health Equity.

Tiffani J Bright1, Keith C Norris2

  • 1Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, California, USA.

Annual Review of Medicine
|October 20, 2025
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) can improve health but may worsen disparities for minority groups. Strategies for equitable health AI involve applying an equity lens and community engagement to ensure AI benefits all populations.

Keywords:
AIartificial intelligencebiashealth equityoutcomes

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Last Updated: Jan 14, 2026

High-definition Transcranial Direct Current Stimulation over Right Dorsolateral Prefrontal Cortex to Enhance Metacognitive Sensitivity
06:11

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Published on: September 26, 2025

813

Area of Science:

  • Biomedical research
  • Public health
  • Clinical care

Background:

  • Artificial intelligence (AI) offers significant potential to improve health outcomes and advance health equity by analyzing complex health data.
  • Concerns exist that AI may exacerbate existing health disparities, particularly for racial and ethnic minorities, individuals with disabilities, and low-income populations.
  • Biased or incomplete data used in AI development can lead to inequitable health outcomes.

Purpose of the Study:

  • To highlight strategies for developing and implementing equitable health AI.
  • To ensure AI technologies enhance health outcomes for all populations, particularly underserved groups.

Main Methods:

  • Review of current literature and strategies for equitable health AI.
  • Emphasis on applying an equity lens throughout the AI life cycle.
  • Highlighting the importance of meaningful community engagement.

Main Results:

  • Equitable health AI requires proactive measures to mitigate bias and ensure fairness.
  • Integrating an equity lens from data collection to deployment is crucial.
  • Community engagement is essential for developing AI solutions that meet diverse needs.

Conclusions:

  • AI has the potential to revolutionize healthcare, but careful consideration of equity is paramount.
  • Implementing specific strategies can help prevent AI from worsening health disparities.
  • Collaborative efforts involving affected communities are key to achieving equitable health AI.