publications

2023

1. Automated Detection of Causal Inference Opportunities: Regression Discontinuity Subgroup Discovery

   Tony Liu, Patrick Lawlor, Lyle Ungar, Konrad Kording, and Rahul Ladhania

   Transactions of Machine Learning Research (TMLR), 2023
2. Analyzing text message linguistic features: Do people with depression communicate differently with their close and non-close contacts?

   Jonah Meyerhoff, Tingting Liu, Caitlin Stamatis, Tony Liu, Harry Wang, Yixuan Meng, Brenda Curtis, Chris J Karr, and 3 more authors

   Behavior Research and Therapy, 2023
3. Leveraging Natural Language Processing and Artificial Intelligence to Label Unstructured Data for Risk Prediction

   C Amro, A Desai, P Dattatri, Tony Liu, JY Hsu, RB Broach, LH Ungar, and JP Fischer

   British Journal of Surgery, 2023

2022

1. Automated Machine Learning for Risk Prediction of Incisional Hernia in Abdominal Surgery Patients

   Ankoor A Talwar, Abhishek A Desai, Phoebe B McAuliffe, Tony Liu, Vivek James, Ivona Percec, Robyn B Broach, Lyle Ungar, and 1 more author

   Plastic and Reconstructive Surgery–Global Open, 2022
2. Data-driven exclusion criteria for instrumental variable studies

   Tony Liu, Patrick Lawlor, Lyle Ungar, and Konrad Kording

   Conference on causal learning and reasoning (CLeaR), 2022
3. The relationship between text message sentiment and self-reported depression

   Tony Liu, Jonah Meyerhoff, Johannes C Eichstaedt, Chris J Karr, Susan M Kaiser, Konrad P Kording, David C Mohr, and Lyle H Ungar

   Journal of affective disorders, 2022
4. Prospective associations of text-message-based sentiment with symptoms of depression, generalized anxiety, and social anxiety

   Caitlin A Stamatis, Jonah Meyerhoff, Tingting Liu, Garrick Sherman, Harry Wang, Tony Liu, Brenda Curtis, Lyle H Ungar, and 1 more author

   Depression and anxiety, 2022
5. Neuromatch Academy: a 3-week, online summer school in computational neuroscience

   Bernard Hart, Titipat Achakulvisut, Ayoade Adeyemi, Athena Akrami, Bradly Alicea, Alicia Alonso-Andres, Diego Alzate-Correa, Arash Ash, and 4 more authors

   Journal of Open Source Education, 2022

2021

1. Quantifying causality in data science with quasi-experiments

   Tony Liu, Lyle Ungar, and Konrad Kording

   Nature computational science, 2021
2. Towards Cotenable and Causal Shapley Feature Explanations

   Tony Liu, and Lyle Ungar

   AAAI 2021 Workshop: Trustworthy AI for Healthcare, 2021
3. Evaluation of changes in depression, anxiety, and social anxiety using smartphone sensor features: longitudinal cohort study

   Jonah Meyerhoff, Tony Liu, Konrad P Kording, Lyle H Ungar, Susan M Kaiser, Chris J Karr, and David C Mohr

   Journal of medical Internet research, 2021
4. Machine learning and surgical outcomes prediction: a systematic review

   Omar Elfanagely, Yoshiko Toyoda, Sammy Othman, Joseph A Mellia, Marten Basta, Tony Liu, Konrad Kording, Lyle Ungar, and 1 more author

   Journal of Surgical Research, 2021

2020

1. A web-based automated machine learning platform to analyze liquid biopsy data

   Hanfei Shen, Tony Liu, Jesse Cui, Piyush Borole, Ari Benjamin, Konrad Kording, and David Issadore

   Lab on a Chip, 2020

2019

1. Machine learning for phone-based relationship estimation: the need to consider population heterogeneity

   Tony Liu, Jennifer Nicholas, Max M Theilig, Sharath C Guntuku, Konrad Kording, David C Mohr, and Lyle Ungar

   Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies, 2019