Physicians’ Perceptions of and Satisfaction With Artificial Intelligence in Cancer Treatment: A Clinical Decision Support System Experience and Implications for Low-Middle–Income Countries

Abstract

As technology continues to improve, health care systems have the opportunity to use a variety of innovative tools for decision-making, including artificial intelligence (AI) applications. However, there has been little research on the feasibility and efficacy of integrating AI systems into real-world clinical practice, especially from the perspectives of clinicians who use such tools. In this paper, we review physicians’ perceptions of and satisfaction with an AI tool, Watson for Oncology, which is used for the treatment of cancer. Watson for Oncology has been implemented in several different settings, including Brazil, China, India, South Korea, and Mexico. By focusing on the implementation of an AI-based clinical decision support system for oncology, we aim to demonstrate how AI can be both beneficial and challenging for cancer management globally and particularly for low-middle–income countries. By doing so, we hope to highlight the need for additional research on user experience and the unique social, cultural, and political barriers to the successful implementation of AI in low-middle–income countries for cancer care.

Are physicians ready for precision antibiotic prescribing? A qualitative analysis of the acceptance of artificial intelligence-enabled clinical decision support systems in India and Singapore

“…With regard to desirable features of AI-enabled CDSSs, a unique theme from the interviews with Indian physicians was the tool's ability to provide an antibiotic of choice after weighing the cost of medicines with the socioeconomic situation of the patient. A recent study about physicians’ perceptions on the use of an AI-enabled CDSS for oncology across India, China, Brazil, South Korea, and Mexico also reported cost consideration as a desirable feature [28] . This theme relates to the local context of poverty and out-of-pocket expenditure for medicines in India which is vastly different from the context in Singapore.…”

Physicians' Perceptions and Expectations of an Artificial Intelligence-Based Clinical Decision Support System in Cancer Care in an Underserved Setting

“…Several examples of localization-related challenges have been reported in studies conducted in countries such as Mexico and China, 41,47 and our recently published review includes additional examples. 48 Prior studies have also demonstrated how implementation and the use of AI-based tools in resource-poor countries require a strong understanding of local social contexts, infrastructure requirements, and availability of other resources. 21,49 In particular, there is an important need to assess the role of local social and cultural context in training an AI tool that has been developed in a Western setting.…”

Artificial Intelligence in the Era of 4ir: Drivers, Challenges and Opportunities

“…By analysing vast datasets of medical literature, clinical trial data, and patient records, Watson for Oncology provides evidence-based treatment recommendations, enhancing the precision and efficacy of cancer care. In finance, JPMorgan Chase provides a notable example of successful AI implementation (Emani et al, 2022;Kann et al, 2021). The bank employs machine learning algorithms to analyse customer data, detect patterns of fraudulent activities, and enhance cybersecurity.…”