‪Mariko Makhmutova‬ - ‪Google Scholar‬

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	All	Since 2019
Citations	18	18
h-index	2	2
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2021202220231 5 12

Co-authors

Raghu KainkaryamJ&J; Evidation Health; P&G; U of M; BHUVerified email at umich.edu
Martin JaggiEPFLVerified email at epfl.ch
ieuan clayVivoSense, ETHZVerified email at vivosense.com

Mariko Makhmutova

Mariko Makhmutova

Verified email at alumni.epfl.ch

data science digital health


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Prediction of self-reported depression scores using person-generated health data from a virtual 1-year mental health observational study M Makhmutova, R Kainkaryam, M Ferreira, J Min, M Jaggi, I Clay Proceedings of the 2021 Workshop on Future of Digital Biomarkers, 4-11, 2021	8	2021
Predicting changes in depression severity using the PSYCHE-D (prediction of severity change-depression) model involving person-generated health data: longitudinal case-control … M Makhmutova, R Kainkaryam, M Ferreira, J Min, M Jaggi, I Clay JMIR mHealth and uHealth 10 (3), e34148, 2022	7	2022
Predicting changes in depression using person-generated health data M Makhmutova	2	2021
PSYCHE-D: predicting change in depression severity using person-generated health data M Makhmutova, R Kainkaryam, M Ferreira, J Min, M Jaggi, I Clay Available at SSRN 3889996, 2022	1	2022

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