17 citations · 29 across the 4 of their papers we have counts for
4 papers
Indicators of retention in remote digital health studies: A cross-study evaluation of 100,000 participants
Abhishek Pratap, Elias Chaibub Neto, Phil Snyder +11
Digital technologies such as smartphones are transforming the way scientists conduct biomedical research using real-world data. Several remotely-conducted studies have recruited th…
Using permutations to assess confounding in machine learning applications for digital health
Elias Chaibub Neto, Abhishek Pratap, Thanneer M Perumal +4
Clinical machine learning applications are often plagued with confounders that can impact the generalizability and predictive performance of the learners. Confounding is especially…
Learning Disease vs Participant Signatures: a permutation test approach to detect identity confounding in machine learning diagnostic applications
Elias Chaibub Neto, Abhishek Pratap, Thanneer M Perumal +6
Recently, Saeb et al (2017) showed that, in diagnostic machine learning applications, having data of each subject randomly assigned to both training and test sets (record-wise data…
On the analysis of personalized medication response and classification of case vs control patients in mobile health studies: the mPower case study
Elias Chaibub Neto, Thanneer M Perumal, Abhishek Pratap +3
In this work we provide a couple of contributions to the analysis of longitudinal data collected by smartphones in mobile health applications. First, we propose a novel statistical…