User profiles for Sohrab Saeb

Sohrab Saeb

Data Scientist, Verily Life Sciences
Verified email at google.com
Cited by 1966

[PDF][PDF] Using and understanding cross-validation strategies. Perspectives on Saeb et al.

MA Little, G Varoquaux, S Saeb, L Lonini… - …, 2017 - academic.oup.com
This three-part review takes a detailed look at the complexities of cross-validation, fostered
by the peer review of Saeb et al.’s paper entitled “The need to approximate the use-case in …

[HTML][HTML] Mobile phone sensor correlates of depressive symptom severity in daily-life behavior: an exploratory study

S Saeb, M Zhang, CJ Karr, SM Schueller… - Journal of medical …, 2015 - jmir.org
Background: Depression is a common, burdensome, often recurring mental health disorder
that frequently goes undetected and untreated. Mobile phones are ubiquitous and have an …

[HTML][HTML] The relationship between mobile phone location sensor data and depressive symptom severity

S Saeb, EG Lattie, SM Schueller, KP Kording, DC Mohr - PeerJ, 2016 - peerj.com
Background Smartphones offer the hope that depression can be detected using passively
collected data from the phone sensors. The aim of this study was to replicate and extend …

The need to approximate the use-case in clinical machine learning

S Saeb, L Lonini, A Jayaraman, DC Mohr… - …, 2017 - academic.oup.com
The availability of smartphone and wearable sensor technology is leading to a rapid
accumulation of human subject data, and machine learning is emerging as a technique to map …

[HTML][HTML] Relationship between sleep quality and mood: ecological momentary assessment study

S Triantafillou, S Saeb, EG Lattie, DC Mohr… - JMIR mental …, 2019 - mental.jmir.org
Background: Sleep disturbances play an important role in everyday affect and vice versa.
However, the causal day-to-day interaction between sleep and mood has not been thoroughly …

[HTML][HTML] Mobile phone detection of semantic location and its relationship to depression and anxiety

S Saeb, EG Lattie, KP Kording… - JMIR mHealth and …, 2017 - mhealth.jmir.org
Background: Is someone at home, at their friend’s place, at a restaurant, or enjoying the
outdoors? Knowing the semantic location of an individual matters for delivering medical …

The relationship between clinical, momentary, and sensor-based assessment of depression

S Saeb, M Zhang, M Kwasny, CJ Karr… - 2015 9th …, 2015 - ieeexplore.ieee.org
The clinical assessment of severity of depressive symptoms is commonly performed with
standardized self-report questionnaires, most notably the patient health questionnaire (PHQ-9), …

Voodoo machine learning for clinical predictions

S Saeb, L Lonini, A Jayaraman, DC Mohr, KP Kording - Biorxiv, 2016 - biorxiv.org
The availability of smartphone and wearable sensor technology is leading to a rapid accumulation
of human subject data, and machine learning is emerging as a technique to map that …

[HTML][HTML] Scalable passive sleep monitoring using mobile phones: opportunities and obstacles

S Saeb, TR Cybulski, SM Schueller, KP Kording… - Journal of medical …, 2017 - jmir.org
Background Sleep is a critical aspect of people’s well-being and as such assessing sleep is
an important indicator of a person’s health. Traditional methods of sleep assessment are …

[HTML][HTML] A holistic approach for suppression of COVID-19 spread in workplaces and universities

…, D Winter, S Nickels, R Levy, B Fu, M Burq, S Saeb… - PloS one, 2021 - journals.plos.org
As society has moved past the initial phase of the COVID-19 crisis that relied on broad-spectrum
shutdowns as a stopgap method, industries and institutions have faced the daunting …