Abstract
Personalized medicine tailors treatment to individual characteristics, leveraging advances in digitized healthcare and AI. This study highlights the role of digital biomarkers, phenotypes, and twins in enhancing healthcare personalization. Despite their potential, challenges like ambiguous definitions hinder their application. Through a systematic literature review, this research explores these constructs' distinctions and applications, aiming to define and classify them clearly. It emphasizes the need for a common language, interdisciplinary collaboration, and effective treatment strategies. The study also underscores the importance of data quality and ethical data use, contributing to the coherent integration of digital health constructs into personalized medicine.
Recommended Citation
Kählig, Maren; Schlieter, Hannes; Wendt, Karsten; and Hickmann, Emily, "Digital dimensions in medicine: exploring the interplay of biomarkers, phenotypes, and twins" (2024). Wirtschaftsinformatik 2024 Proceedings. 32.
https://aisel.aisnet.org/wi2024/32