123 citations
- King's College LondonGB5 papers
- Parc Sanitari Sant Joan de DéuES5 papers
- South London and Maudsley NHS Foundation TrustGB5 papers
- University College LondonGB5 papers
- Centro de Investigación Biomédica en Red de Salud MentalES4 papers
- KU LeuvenBE4 papers
- LAB University of Applied SciencesFI4 papers
- Universitat de BarcelonaES4 papers
- Health Data Research UKGB3 papers
- Lundbeck (Denmark)DK3 papers
- National Health ServiceGB3 papers
- Northwestern UniversityUS3 papers
12 papers
Challenges in Using mHealth Data From Smartphones and Wearable Devices to Predict Depression Symptom Severity: Retrospective Analysis
Shaoxiong Sun, Amos A. Folarin, Yuezhou Zhang +28
A number of challenges exist for the analysis of mHealth data: maintaining participant engagement over extended time periods and therefore understanding what constitutes an accepta…
Designing an exploratory phase 2b platform trial in NASH with correlated, co-primary binary endpoints
Elias Laurin Meyer, Peter Mesenbrink, Nicholas A. Di Prospero +5
Non-alcoholic steatohepatitis (NASH) is the progressive form of nonalcoholic fatty liver disease (NAFLD) and a disease with high unmet medical need. Platform trials provide great b…
Massive Parallelization of Massive Sample-size Survival Analysis
Jianxiao Yang, Martijn J. Schuemie, Xiang Ji +1
Large-scale observational health databases are increasingly popular for conducting comparative effectiveness and safety studies of medical products. However, increasing number of p…
Associations between depression symptom severity and daily-life gait characteristics derived from long-term acceleration signals in real-world settings
Yuezhou Zhang, Amos A Folarin, Shaoxiong Sun +27
Gait is an essential manifestation of depression. Laboratory gait characteristics have been found to be closely associated with depression. However, the gait characteristics of dai…
Adjusting for indirectly measured confounding using large-scale propensity scores
Linying Zhang, Yixin Wang, Martijn Schuemie +2
Confounding remains one of the major challenges to causal inference with observational data. This problem is paramount in medicine, where we would like to answer causal questions f…
Predicting Depressive Symptom Severity through Individuals' Nearby Bluetooth Devices Count Data Collected by Mobile Phones: A Preliminary Longitudinal Study
Yuezhou Zhang, Amos A Folarin, Shaoxiong Sun +21
The Bluetooth sensor embedded in mobile phones provides an unobtrusive, continuous, and cost-efficient means to capture individuals' proximity information, such as the nearby Bluet…