Harnessing AI for health equity in oncology research and practice.

2018 
67Background: Recent advances in artificial intelligence (AI) carry underexplored practical and ethical implications for the practice of clinical oncology. As oncologic applications of AI proliferate, a framework for guiding their ethical implementations and equitable distribution will be crucial. Methods: We reviewed the current landscape of AI applications in oncology research and clinical practice by reviewing the current body of evidence in PubMed and Medline. Key ethical challenges and opportunities to address health equity are critically evaluated and highlighted. Ethical implications for patients, clinicians and society at large are delineated, with particular focus on the impact and ramifications of AI with respect to healthcare disparities and equity of oncology care delivery. Results: Growing concerns that AI may widen disparities in oncologic care by virtue of lack of affordability, inconsistent accessibility and biased machine-learning models are addressed. Although there is potential for AI t...
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    0
    References
    0
    Citations
    NaN
    KQI
    []