Domain extension learning device, domain extension learning method, and recording medium

Abstract

In a domain extension learning device, a generation means generates pseudo medical examination data. A prediction means predicts a domain from the pseudo medical examination data. A calculation means calculates the difference between the predicted domain and the specified domain. An update means updates the parameters of the generation means based on the difference. The generation means may comprise a deep learning model. According to the domain extension learning device, it is possible to generate pseudo data of an unknown domain. As a result, the user can acquire learning data including a wide variety of domains, and can optimize a disease risk prediction model. Furthermore, by using this disease risk prediction model, it is possible to support the user's decision making.

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