Abhishek Pratap

According to our database, Abhishek Pratap authored at least 9 papers between 2015 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

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, Katie M. White, Carolin Oetzmann, Alina Ivan, Femke Lamers, Sara Siddi, Carla Hernández Rambla, Sara Simblett, Raluca Nica, David C. Mohr, Inez Myin-Germeys, Til Wykes, Josep Maria Haro, Brenda W. J. H. Penninx, Peter Annas, Vaibhav A. Narayan, Matthew Hotopf, Richard J. B. Dobson

npj Digit. Medicine, 2023

2022

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

Proceedings of the AMIA 2022, 2022

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, Pat A. Areán, Larsson Omberg

npj Digit. Medicine, 2020

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

Proceedings of the PervasiveHealth '20: 14th EAI International Conference on Pervasive Computing Technologies for Healthcare, 2020

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

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, Pat A. Areán, Larsson Omberg

CoRR, 2019

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

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

2017

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

Proceedings of the Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers, 2017

2015

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, Michael P. Menden, Pablo Meyer, Raquel Norel, Abhishek Pratap, Robert J. Prill, Matthew T. Weirauch, James C. Costello, Gustavo Stolovitzky, Julio Saez-Rodriguez

F1000Research, 2015