Bridging the gaps: Overcoming challenges of implementing AI in healthcare.

Journal: Med (New York, N.Y.)
PMID: 40220747

Abstract

Artificial intelligence (AI) in healthcare promises transformative advancements, from enhancing diagnostics to optimizing personalized treatments. Realizing its full potential, however, requires addressing key challenges, including explainability, bias & fairness, infrastructure, privacy, security, as well as ethical, regulatory and educational challenges. Bridging these gaps is essential to ensure AI's equitable and effective integration into clinical practice.

Authors

  • Xiaoyun Huang
    Center for Systems Biology, Intelliphecy, Main Building, Beishan Industrial Zone, Shenzhen, Guangdong, China.
  • Lei Gu
    School of Automation, Central South University, Changsha 410083, China.
  • Jian Sun
    Department Of Computer Science, University of Denver, 2155 E Wesley Ave, Denver, Colorado, 80210, United States of America.
  • Roland Eils
    Center for Digital Health, Berlin Institute of Health, Charité - University Medicine Berlin, Berlin, Germany. roland_eils@fudan.edu.cn.

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