Automated regulatory classification of mobile medical apps

Presentation Type

Abstract

Faculty Advisor

Raina Samuel

Access Type

Event

Start Date

25-4-2025 12:00 PM

End Date

25-4-2025 1:00 PM

Description

Mobile medical applications provide a variety of functionalities for users, from managing critical personal data to providing basic medical information. However, due to the variety of functionalities and lack of consistent and concrete regulatory oversight across app marketplaces, medical apps potentially pose a threat to users who are generally unaware of app capabilities. Therefore, in order to help legal experts quickly identify which regulatory body applies to the wide variety of medical apps used by consumers, we present a method for converting and plotting the prose of both app descriptions and regulatory legalese into a vector space in order to facilitate rapid cosine similarity scoring. Our study demonstrates how to automate regulation of mobile medical apps using descriptions with the language of regulatory bodies. Our results make apparent a need for comprehensive regulatory oversight of medical apps, with 54.8 % of apps on Google Play and 58% of apps on the Apple App Store.

Comments

Poster presentation at the 2025 Student Research Symposium.

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Apr 25th, 12:00 PM Apr 25th, 1:00 PM

Automated regulatory classification of mobile medical apps

Mobile medical applications provide a variety of functionalities for users, from managing critical personal data to providing basic medical information. However, due to the variety of functionalities and lack of consistent and concrete regulatory oversight across app marketplaces, medical apps potentially pose a threat to users who are generally unaware of app capabilities. Therefore, in order to help legal experts quickly identify which regulatory body applies to the wide variety of medical apps used by consumers, we present a method for converting and plotting the prose of both app descriptions and regulatory legalese into a vector space in order to facilitate rapid cosine similarity scoring. Our study demonstrates how to automate regulation of mobile medical apps using descriptions with the language of regulatory bodies. Our results make apparent a need for comprehensive regulatory oversight of medical apps, with 54.8 % of apps on Google Play and 58% of apps on the Apple App Store.