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Open AccessArticle

Cancer Prevention Using Machine Learning, Nudge Theory and Social Impact Bond

Department of Innovation Science, School of Environment and Society, Tokyo Institute of Technology, Tokyo 152-8850, Japan
Cancer Scan, Co., Ltd., Tokyo 141-0031, Japan
Life Style by Design Research Unit, Institute for Future Initiatives, the University of Tokyo, Tokyo 113-0033, Japan
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(3), 790;
Received: 2 December 2019 / Revised: 21 January 2020 / Accepted: 23 January 2020 / Published: 28 January 2020
(This article belongs to the Special Issue E-Health Services)
There have been prior attempts to utilize machine learning to address issues in the medical field, particularly in diagnoses using medical images and developing therapeutic regimens. However, few cases have demonstrated the usefulness of machine learning for enhancing health consciousness of patients or the public in general, which is necessary to cause behavioral changes. This paper describes a novel case wherein the uptake rate for colorectal cancer examinations has significantly increased due to the application of machine learning and nudge theory. The paper also discusses the effectiveness of social impact bonds (SIBs) as a scheme for realizing these applications. During a healthcare SIB project conducted in the city of Hachioji, Tokyo, machine learning, based on historical data obtained from designated periodical health examinations, digitalized medical insurance receipts, and medical examination records for colorectal cancer, was used to deduce segments for whom the examination was recommended. The result revealed that out of the 12,162 people for whom the examination was recommended, 3264 (26.8%) received it, which exceeded the upper expectation limit of the initial plan (19.0%). We conclude that this was a successful case that stimulated discussion on potential further applications of this approach to wider regions and more diseases. View Full-Text
Keywords: disease prevention; machine learning; nudge theory; medical data; social impact bond disease prevention; machine learning; nudge theory; medical data; social impact bond
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Misawa, D.; Fukuyoshi, J.; Sengoku, S. Cancer Prevention Using Machine Learning, Nudge Theory and Social Impact Bond. Int. J. Environ. Res. Public Health 2020, 17, 790.

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