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

Bibliographic Details
Title: Physicians’ Perceptions of and Satisfaction With Artificial Intelligence in Cancer Treatment: A Clinical Decision Support System Experience and Implications for Low-Middle–Income Countries
Authors: Srinivas Emani, Angela Rui, Hermano Alexandre Lima Rocha, Rubina F Rizvi, Sergio Ferreira Juaçaba, Gretchen Purcell Jackson, David W Bates
Source: JMIR Cancer, Vol 8, Iss 2, p e31461 (2022)
Publisher Information: JMIR Publications, 2022.
Publication Year: 2022
Collection: LCC:Neoplasms. Tumors. Oncology. Including cancer and carcinogens
Subject Terms: Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
More Details: 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.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2369-1999
Relation: https://cancer.jmir.org/2022/2/e31461; https://doaj.org/toc/2369-1999
DOI: 10.2196/31461
Access URL: https://doaj.org/article/e59efee96efd4244ac1c6909446d358d
Accession Number: edsdoj.59efee96efd4244ac1c6909446d358d
Database: Directory of Open Access Journals
More Details
ISSN:23691999
DOI:10.2196/31461
Published in:JMIR Cancer
Language:English