DREAMTools: a Python package for scoring collaborative challenges. - Thomas Cokelaer; Mukesh Bansal; Christopher Bare; Erhan Bilal; Brian M. Bot; Elias Chaibub Neto; Federica Eduati; Mehmet Gönen; Steven M. Hill; Bruce R. Hoff; Jonathan R. Karr; Robert Küffner; et al. (F1000Research, 2015)

The feasibility of using smartphones to assess and remediate depression in Hispanic/Latino individuals nationally. - Abhishek Pratap; Joaquin A. Anguera; Brenna N. Renn; Elias Chaibub Neto; Joshua Volponi; Sean D. Mooney; Pat A. Areán (UbiComp/ISWC Adjunct, 2017)

A Permutation Approach to Assess Confounding in Machine Learning Applications for Digital Health. - Elias Chaibub Neto; Abhishek Pratap; Thanneer M. Perumal; Meghasyam Tummalacherla; Brian M. Bot; Lara M. Mangravite; Larsson Omberg (KDD, 2019)

Indicators of retention in remote digital health studies: A cross-study evaluation of 100, 000 participants. - Abhishek Pratap; Elias Chaibub Neto; Phil Snyder; Carl Stepnowsky; Noémie Elhadad; Daniel Grant; Matthew H. Mohebbi; Sean D. Mooney; Christine Suver; John Wilbanks; Lara M. Mangravite; Patricki J. Heagerty; et al. (CoRR, 2019)

Detecting the impact of subject characteristics on machine learning-based diagnostic applications. - Elias Chaibub Neto; Abhishek Pratap; Thanneer M. Perumal; Meghasyam Tummalacherla; Phil Snyder; Brian M. Bot; Andrew D. Trister; Stephen H. Friend; Lara M. Mangravite; Larsson Omberg (npj Digit. Medicine, 2019)

Understanding Participant Needs for Engagement and Attitudes towards Passive Sensing in Remote Digital Health Studies. - Samantha Kolovson; Abhishek Pratap; Jaden Duffy; Ryan Allred; Sean A. Munson; Patricia A. Areán (PervasiveHealth, 2020)

Indicators of retention in remote digital health studies: a cross-study evaluation of 100, 000 participants. - Abhishek Pratap; Elias Chaibub Neto; Phil Snyder; Carl Stepnowsky; Noémie Elhadad; Daniel Grant; Matthew H. Mohebbi; Sean D. Mooney; Christine Suver; John Wilbanks; Lara M. Mangravite; Patrick J. Heagerty; et al. (npj Digit. Medicine, 2020)

Geospatial divide in real-world EHR data: Analytical workflow to assess regional biases and potential impact on health equity. - Serena Jinchen Xie; Flavia Kapos; Stephen J. Mooney; Sean D. Mooney; Kari A. Stephens; Andrea L. Hartzler; Abhishek Pratap (AMIA, 2022)

Long-term participant retention and engagement patterns in an app and wearable-based multinational remote digital depression study. - Yuezhou Zhang; Abhishek Pratap; Amos A. Folarin; Shaoxiong Sun; Nicholas Cummins; Faith Matcham; Srinivasan Vairavan; Judith Dineley; Yatharth Ranjan; Zulqarnain Rashid; Pauline Conde; Callum L. Stewart; et al. (npj Digit. Medicine, 2023)

A Novel Unsupervised Machine Learning Approach to Assess Postural Dynamics in Euthymic Bipolar Disorder. - Ramzi Halabi; Christina Gonzalez-Torres; Stephane MacLean; M. Ishrat Husain; Abhishek Pratap; Martin Alda; Benoit H. Mulsant; Abigail Ortiz (IEEE J. Biomed. Health Informatics, 2024)

Comparative Assessment of Multimodal Sensor Data Quality Collected Using Android and iOS Smartphones in Real-World Settings. - Ramzi Halabi; Rahavi Selvarajan; Zixiong Lin; Calvin Herd; Xueying Li; Jana Kabrit; Meghasyam Tummalacherla; Elias Chaibub Neto; Abhishek Pratap (Sensors, 2024)