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Rui A, Emani S, Rocha HAL, Rizvi RF, Juaçaba SF, Jackson GP, Bates DW
Physicians’ Perceptions of and Satisfaction With Artificial Intelligence in Cancer Treatment: A Clinical Decision Support System Experience and Implications for Low-Middle–Income Countries
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
The Role of Artificial Intelligence (AI) in Cancer Treatment in Low-Middle Income Countries: The Watson for Oncology (WfO) Experience
Angela Rui;
Srinivas Emani;
Hermano Alexandre Lima Rocha;
Rubina F. Rizvi;
Sergio Ferreira Juaçaba;
Gretchen Purcell Jackson;
David W. Bates
ABSTRACT
As technology continues to improve, healthcare systems have the opportunity to utilize a variety of innovative tools for decision making that extend beyond traditional clinical decision support systems (CDSSs). The feasibility and efficacy integrating artificial intelligence (AI) systems into medical practice has shown variable success, especially in resource-poor areas. In this paper, we cover the existing challenges surrounding cancer treatment in low-middle income countries (LMICs). By focusing on the implementation of an AI-based CDSS for oncology, we aim to demonstrate how AI can be both beneficial and challenging for cancer management globally. Additionally, we summarize current physician perspectives from China, India, Brazil, Thailand, and Mexico in regard to their experiences and recommendations for improving the system. By doing so, we hope to highlight the need for additional research on user experience and unique cultural barriers for the successful implementation of AI in LMICs.
Citation
Please cite as:
Rui A, Emani S, Rocha HAL, Rizvi RF, Juaçaba SF, Jackson GP, Bates DW
Physicians’ Perceptions of and Satisfaction With Artificial Intelligence in Cancer Treatment: A Clinical Decision Support System Experience and Implications for Low-Middle–Income Countries