Systematic Assessment of Analytical Methods for Drug Sensitivity Prediction from Cancer Cell Line Data. - In Sock Jang; Elias Chaibub Neto; Justin Guinney; Stephen H. Friend; Adam A. Margolin (Pacific Symposium on Biocomputing, 2014)

The Stream Algorithm: Computationally Efficient Ridge-Regression via Bayesian Model Averaging, and Applications to Pharmacogenomic Prediction of Cancer Cell Line Sensitivity. - Elias Chaibub Neto; In Sock Jang; Stephen H. Friend; Adam A. Margolin (Pacific Symposium on Biocomputing, 2014)

Identifying robust clusters and multi-community nodes by combining top-down and bottom-up approaches to clustering. - Chris Gaiteri; Mingming Chen; Boleslaw K. Szymanski; Konstantin Kuzmin; Jierui Xie; Changkyu Lee; Timothy Blanche; Elias Chaibub Neto; Su-Chun Huang; Thomas J. Grabowski; Tara M. Madhyastha; Vitalina Komashko (CoRR, 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; et al. (F1000Research, 2015)

Personalized Hypothesis Tests for Detecting Medication Response in Parkinson Disease Patients Using iPhone Sensor Data. - Elias Chaibub Neto; Brian M. Bot; Thanneer M. Perumal; Larsson Omberg; Justin Guinney; Mike Kellen; Arno Klein; Stephen H. Friend; Andrew D. Trister (PSB, 2016)

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)

Mindboggling morphometry of human brains. - Arno Klein; Satrajit S. Ghosh; Forrest Sheng Bao; Joachim Giard; Yrjö Häme; Eliezer Stavsky; Noah Lee; Brian Rossa; Martin Reuter 001; Elias Chaibub Neto; Anisha Keshavan (PLoS Comput. Biol., 2017)

Remote Assessment, in Real-World Setting, of Tremor Severity in Parkinson's Disease Patients Using Smartphone Inertial Sensors. - Thanneer M. Perumal; Meghasyam Tummalacherla; Phil Snyder; Elias Chaibub Neto; Earl Ray Dorsey; Lara M. Mangravite; Larsson Omberg (UbiComp/ISWC Adjunct, 2018)

Detecting Learning vs Memorization in Deep Neural Networks using Shared Structure Validation Sets. - Elias Chaibub Neto (CoRR, 2018)

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)

A Causal Look at Statistical Definitions of Discrimination. - Elias Chaibub Neto (KDD, 2020)

Counterfactual confounding adjustment for feature representations learned by deep models: with an application to image classification tasks. - Elias Chaibub Neto (CoRR, 2020)

Stable predictions for health related anticausal prediction tasks affected by selection biases: the need to deconfound the test set features. - Elias Chaibub Neto; Phil Snyder; Solveig K. Sieberts; Larsson Omberg (CoRR, 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)

Causality-aware counterfactual confounding adjustment as an alternative to linear residualization in anticausal prediction tasks based on linear learners. - Elias Chaibub Neto (ICML, 2021)

Crowdsourcing digital health measures to predict Parkinson's disease severity: the Parkinson's Disease Digital Biomarker DREAM Challenge. - Solveig K. Sieberts; Jennifer Schaff; Marlena Duda; Bálint Á Pataki; Ming Sun; Phil Snyder; Jean-Francois Daneault; Federico Parisi; Gianluca Costante; Udi Rubin; Peter Banda; Yooree Chae; et al. (npj Digit. Medicine, 2021)

Causality-Aware Predictions in Static Anticausal Machine Learning Tasks. - Elias Chaibub Neto (IEEE Trans. Neural Networks Learn. Syst., 2024)

Statistical disclosure control for numeric microdata via sequential joint probability preserving data shuffling. - Elias Chaibub Neto (Trans. Data Priv., 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)

A novel estimator for the two-way partial AUC. - Elias Chaibub Neto; Vijay Yadav; Solveig K. Sieberts; Larsson Omberg (BMC Medical Informatics Decis. Mak., 2024)