Other Research

Conferences

Jinsung Yoon, James Jordon, Mihaela van der Schaar, “ASAC: Active Sensing using Actor-Critic Models,” Machine Learning for Healthcare Conference (MLHC), 2019. [Paper link]

Competitions

James Jordon, Daniel Jarrett, Jinsung Yoon, Tavian Barnes, Paul Elbers, Patrick Thoral, Ari Ercole, Cheng Zhang, Danielle Belgrave, Mihaela van der Schaar, “Hide-and-Seek Privacy Challenge Synthetic Data Generation vs. Patient Re-identification with Clinical Time-series Data,” NeurIPS 2020 Competition Track (NeurIPS), 2020. [Paper link] [Blog link] [Code link]

Workshops

Zach Izzo, Jinsung Yoon, Sercan O Arik, James Zou, “Provable Membership Inference Privacy,” NeurIPS 2022 Trustworthy and Socially Responsible Machine Learning Workshop (NeurIPS-TSRML), 2022. [Paper link]

Vishnu Suresh Lokhande, Kihyuk Sohn, Jinsung Yoon, Madeleine Udell, Chen-Yu Lee, Tomas Pfister, “Towards Group Robustness in the Presence of Partial Group Labels” ICML 2022 Workshop on Spurious Correlations, Invariance and Stability (SCIS), 2022. [Paper link]

Sercan O. Arik, Chun-Liang Li, Martin Nikoltchev, Rajarishi Sinha, Arkady Epshteyn, Jinsung Yoon, Long Le, Vikas Menon, Shashank Singh, Yash Sonthalia, Hootan Nakhost, Leyou Zhang, Elli Kanal, Tomas Pfister, “Interpretable Covid-19 Forecasting,” ICML 2020 Workshop on Healthcare Systems, Population Health, and the role of Health-tech, 2020. [Paper link]

Daniel Jarrett, Jinsung Yoon, M. van der Schaar, “MATCH-Net: Dynamic Prediction in Survival Analysis using Convolutional Neural Networks,” NeurIPS Machine Learning for Health Workshop, 2018. [Paper link] [Poster link] – Selected as spotlight talk

Carl Rietschel, Jinsung Yoon, Mihaela van der Schaar, “Feature Selection for Survival Analysis with Competing Risks using Deep Learning,” NeurIPS Machine Learning for Health Workshop, 2018. [Paper link] [ Code link ]

James Jordon, Jinsung Yoon, Mihaela van der Schaar, “Measuring the quality of Synthetic data for use in competitions,” KDD Workshop on Machine Learning for Medicine and Healthcare, 2018. [Paper link] [Code link]

Jinsung Yoon, Mihaela van der Schaar, “E-RNN: Entangled Recurrent Neural Networks for Causal Prediction,” ICML Workshop on Principled Approaches to Deep Learning, 2017. [Paper link]

Jinsung Yoon, William R. Zame, Mihaela van der Schaar, “Multi-directional Recurrent Neural Networks: A Novel Method for Estimating Missing Data,” ICML Time Series Workshop, 2017. [Paper link]

Ahmed M. Alaa, Jinsung Yoon, Scott Hu, Mihaela van der Schaar, “A Semi-Markov Switching Linear Gaussian Model for Censored Physiological Data,” NeurIPS – Workshop on Machine Learning for Health, 2016. [Paper link]

Ahmed M. Alaa, Jinsung Yoon, Scott Hu, Mihaela van der Schaar, “Personalized Risk Scoring for Critical Care Patients using Mixtures of Gaussian Process Experts ,” ICML 2016 Workshop on Computational Frameworks for Personalization, 2016. [Paper link]

Cem Tekin, Jinsung Yoon, Mihaela van der Schaar, “Adaptive ensemble learning with confidence bounds for personalized diagnosis ,” AAAI Workshop on Expanding the Boundaries of Health Informatics using AI (HIAI’16), 2016. [Paper link]

Clinical Conferences & Abstract

Edina Cenko, Mihaela van der Schaar, Jinsung Yoon, Olivia Manfrini, Zorana Vasiljevic, Sasko Kedev, Marija Vavlukis, Milika Asanin, Davor Milicic, Lina Badimon and Raffaele Bugiardini, “De novo” Heart Failure: a Mechanism Underscoring Sex Differences in Outcomes after ST-Segment Elevation Myocardial Infarction,” Journal of the American College of Cardiology (JACC), 2019. [Paper link]

Raffaele Bugiardini, Edina Cenko, Jinsung Yoon, Beatrice Ricci, Davor Milicic, Sasko Kedev, Zorana Vasiljevic, Olivia Manfrini, Mihaela van der Schaar and Lina Badimon, “Late PCI in STEMI: A Complex Interaction between Delay and Age,” American College of the Cardiology (ACC) – 67th Annual Scientific Session & Expo; Journal of the American College of Cardiology, 2018. [Paper link]

Beatrice Ricci, Mihaela van der Schaar, Jinsung Yoon, Edina Cenko, Zorana Vasiljevic, Maria Dorobantu, Marija Zdravkovic, Sasko Kedev, Oliver Kalpak, Davor Milicic, Olivia Manfrini, Lina Badimon, and Raffaele Bugiardini, “Machine Learning Techniques for Risk Stratification of Non-ST-Elevation Acute Coronary Syndrome: The Role of Diabetes and Age,” American Heart Association Scientific Session - Circulation, 2017 [Paper link]

Amitava Banerjee, Jinsung Yoon, William R. Zame, Martin Cadeiras, Ahmed M. Alaa, Mihaela van der Schaar, “Personalized Risk Prediction using Predictive Pursuit Machine Learning: A Pilot Study in Cardiac Transplantation,” European Society of Cardiology Congress, 2017. – Selected as Best Posters in Advanced Heart Failure.

Mindy K. Ross, Jinsung Yoon, Kyeong Ho Moon, Mihaela van der Schaar, “A Personalized Approach to Asthma Control Over Time: Discovering Phenotypes Using Machine Learning,” American Thoracic Society (ATS) International Conference, 2017. [Paper Link]

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