Causality-aware counterfactual confounding adjustment as an alternative to linear residualization in anticausal prediction tasks based on linear learners.

[BibT_eX]

[DOI]

Elias Chaibub Neto

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Indicators of retention in remote digital health studies: a cross-study evaluation of 100, 000 participants.

[BibT_eX]

[DOI]

npj Digit. Medicine, 2020

Stable predictions for health related anticausal prediction tasks affected by selection biases: the need to deconfound the test set features.

[BibT_eX]

[DOI]

CoRR, 2020

Counterfactual confounding adjustment for feature representations learned by deep models: with an application to image classification tasks.

[BibT_eX]

[DOI]

Elias Chaibub Neto

CoRR, 2020

A Causal Look at Statistical Definitions of Discrimination.

[BibT_eX]

[DOI]

Elias Chaibub Neto

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2019

Detecting the impact of subject characteristics on machine learning-based diagnostic applications.

[BibT_eX]

[DOI]

Elias Chaibub Neto

Abhishek Pratap

Thanneer M. Perumal

Meghasyam Tummalacherla

npj Digit. Medicine, 2019

Indicators of retention in remote digital health studies: A cross-study evaluation of 100, 000 participants.

[BibT_eX]

[DOI]

CoRR, 2019

A Permutation Approach to Assess Confounding in Machine Learning Applications for Digital Health.

[BibT_eX]

[DOI]

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

2018

Detecting Learning vs Memorization in Deep Neural Networks using Shared Structure Validation Sets.

[BibT_eX]

[DOI]

Elias Chaibub Neto

CoRR, 2018

Remote Assessment, in Real-World Setting, of Tremor Severity in Parkinson's Disease Patients Using Smartphone Inertial Sensors.

[BibT_eX]

[DOI]

Thanneer M. Perumal

Meghasyam Tummalacherla

Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers, 2018

2017

Mindboggling morphometry of human brains.

[BibT_eX]

[DOI]

PLoS Comput. Biol., 2017

The feasibility of using smartphones to assess and remediate depression in Hispanic/Latino individuals nationally.

[BibT_eX]

[DOI]

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

2016

Personalized Hypothesis Tests for Detecting Medication Response in Parkinson Disease Patients Using iPhone Sensor Data.

[BibT_eX]

[DOI]

Proceedings of the Biocomputing 2016: Proceedings of the Pacific Symposium, 2016

2015

DREAMTools: a Python package for scoring collaborative challenges.

[BibT_eX]

[DOI]

F1000Research, 2015

Identifying robust clusters and multi-community nodes by combining top-down and bottom-up approaches to clustering.

[BibT_eX]

[DOI]

Chris Gaiteri

Mingming Chen

Boleslaw K. Szymanski

CoRR, 2015

2014

The Stream Algorithm: Computationally Efficient Ridge-Regression via Bayesian Model Averaging, and Applications to Pharmacogenomic Prediction of Cancer Cell Line Sensitivity.

[BibT_eX]

[DOI]

Proceedings of the Biocomputing 2014: Proceedings of the Pacific Symposium, 2014

Systematic Assessment of Analytical Methods for Drug Sensitivity Prediction from Cancer Cell Line Data.

[BibT_eX]

[DOI]

In Sock Jang

Elias Chaibub Neto