Details

Autor(en) / Beteiligte

• Inomata, Takenori
• Nakamura, Masahiro
• Sung, Jaemyoung
• Midorikawa-Inomata, Akie
• Iwagami, Masao
• Fujio, Kenta
• Akasaki, Yasutsugu
• Okumura, Yuichi
• Fujimoto, Keiichi
• Eguchi, Atsuko
• Miura, Maria
• Nagino, Ken
• Shokirova, Hurramhon
• Zhu, Jun
• Kuwahara, Mizu
• Hirosawa, Kunihiko
• Dana, Reza
• Murakami, Akira

Titel

Smartphone-based digital phenotyping for dry eye toward P4 medicine: a crowdsourced cross-sectional study

Ist Teil von

• NPJ digital medicine, 2021-12, Vol.4 (1), p.171-171, Article 171

Ort / Verlag

London: Nature Publishing Group UK

Erscheinungsjahr

2021

Quelle

EZB Free E-Journals

Beschreibungen/Notizen

• Multidimensional integrative data analysis of digital phenotyping is crucial for elucidating the pathologies of multifactorial and heterogeneous diseases, such as the dry eye (DE). This crowdsourced cross-sectional study explored a novel smartphone-based digital phenotyping strategy to stratify and visualize the heterogenous DE symptoms into distinct subgroups. Multidimensional integrative data were collected from 3,593 participants between November 2016 and September 2019. Dimension reduction via Uniform Manifold Approximation and Projection stratified the collected data into seven clusters of symptomatic DE. Symptom profiles and risk factors in each cluster were identified by hierarchical heatmaps and multivariate logistic regressions. Stratified DE subgroups were visualized by chord diagrams, co-occurrence networks, and Circos plot analyses to improve interpretability. Maximum blink interval was reduced in clusters 1, 2, and 5 compared to non-symptomatic DE. Clusters 1 and 5 had severe DE symptoms. A data-driven multidimensional analysis with digital phenotyping may establish predictive, preventive, personalized, and participatory medicine.