Collin M. Stultz

32 papers A* 2C 1Misc 2Journal 19Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Position: Evaluation of ECG Representations Must Be Fixed. CoRR Zachary Berger, Daniel Prakah-Asante, John V. Guttag, Collin M. Stultz
2026	J	`jnl`	Robustness Beyond Known Groups with Low-rank Adaptation. CoRR Abinitha Gourabathina, Hyewon Jeong, Teya S. Bergamaschi, Marzyeh Ghassemi, Collin M. Stultz
2024	—	`conf`	Continuity Contrastive Representations of ECG for Heart Block Detection from Only Lead-I. ML4H@NeurIPS Teya S. Bergamaschi, Collin M. Stultz, Ridwan Alam
2024	J	`jnl`	Detecting QT prolongation From a Single-lead ECG With Deep Learning. CoRR Ridwan Alam, Aaron D. Aguirre, Collin M. Stultz
2024	J	`jnl`	Estimating ECG Intervals from Lead-I Alone: External Validation of Supervised Models. CoRR Ridwan Alam, Collin M. Stultz
2024	—	`conf`	Event-Based Contrastive Learning for Medical Time Series. MLHC Nassim Oufattole, Hyewon Jeong, Matthew B. A. McDermott, Aparna Balagopalan, Bryan Jangeesingh, Marzyeh Ghassemi, Collin M. Stultz
2024	C	`conf`	Heart Block Identification from 12-Lead ECG: Exploring the Generalizability of Self-Supervised AI. BSN Teya S. Bergamaschi, Collin M. Stultz, Ridwan Alam
2024	J	`jnl`	MEDS-Tab: Automated tabularization and baseline methods for MEDS datasets. CoRR Nassim Oufattole, Teya S. Bergamaschi, Aleksia Kolo, Hyewon Jeong, Hanna Gaggin, Collin M. Stultz, Matthew B. A. McDermott
2023	—	`conf`	Deep Metric Learning for the Hemodynamics Inference with Electrocardiogram Signals. MLHC Hyewon Jeong, Collin M. Stultz, Marzyeh Ghassemi
2023	J	`jnl`	Deep Metric Learning for the Hemodynamics Inference with Electrocardiogram Signals. CoRR Hyewon Jeong, Collin M. Stultz, Marzyeh Ghassemi
2023	J	`jnl`	Event-Based Contrastive Learning for Medical Time Series. CoRR Hyewon Jeong, Nassim Oufattole, Aparna Balagopalan, Matthew B. A. McDermott, Payal Chandak, Marzyeh Ghassemi, Collin M. Stultz
2023	—	`conf`	QTNet: Deep Learning for Estimating QT Intervals Using a Single Lead ECG. EMBC Ridwan Alam, Aaron D. Aguirre, Collin M. Stultz
2023	A*	`conf`	Sequential Multi-Dimensional Self-Supervised Learning for Clinical Time Series. ICML Aniruddh Raghu, Payal Chandak, Ridwan Alam, John V. Guttag, Collin M. Stultz
2023	J	`jnl`	Sequential Multi-Dimensional Self-Supervised Learning for Clinical Time Series. CoRR Aniruddh Raghu, Payal Chandak, Ridwan Alam, John V. Guttag, Collin M. Stultz
2022	—	`conf`	Data Augmentation for Electrocardiograms. CHIL Aniruddh Raghu, Divya Shanmugam, Eugene Pomerantsev, John V. Guttag, Collin M. Stultz
2022	J	`jnl`	Data Augmentation for Electrocardiograms. CoRR Aniruddh Raghu, Divya Shanmugam, Eugene Pomerantsev, John V. Guttag, Collin M. Stultz
2022	Misc	`conf`	Feature Selection Based on Subpopulations and Propensity Score Matching: A Coronary Artery Disease Use Case using the UK Biobank. AMIA Uri Kartoun, Paul Myers, Kristen A. Severson, Wangzhi Dai, Kenney Ng, Collin M. Stultz
2022	J	`jnl`	Patient contrastive learning: A performant, expressive, and practical approach to electrocardiogram modeling. PLoS Comput. Biol. Nathaniel Diamant, Erik Reinertsen, Steven Song, Aaron D. Aguirre, Collin M. Stultz, Puneet Batra
2021	J	`jnl`	Learning to Predict with Supporting Evidence: Applications to Clinical Risk Prediction. CoRR Aniruddh Raghu, John V. Guttag, Katherine Young, Eugene Pomerantsev, Adrian V. Dalca, Collin M. Stultz
2021	—	`conf`	Learning to predict with supporting evidence: applications to clinical risk prediction. CHIL Aniruddh Raghu, John V. Guttag, Katherine Young, Eugene Pomerantsev, Adrian V. Dalca, Collin M. Stultz
2021	J	`jnl`	Patient Contrastive Learning: a Performant, Expressive, and Practical Approach to ECG Modeling. CoRR Nathaniel Diamant, Erik Reinertsen, Steven Song, Aaron D. Aguirre, Collin M. Stultz, Puneet Batra
2020	J	`jnl`	Identifying unreliable predictions in clinical risk models. npj Digit. Medicine Paul D. Myers, Kenney Ng, Kristen A. Severson, Uri Kartoun, Wangzhi Dai, Wei Huang, Fred Anderson, Collin M. Stultz
2020	—	`conf`	Quantifying Common Support between Multiple Treatment Groups Using a Contrastive-VAE. ML4H@NeurIPS Wangzhi Dai, Collin M. Stultz
2019	A*	`conf`	Generative Oversampling with a Contrastive Variational Autoencoder. ICDM Wangzhi Dai, Kenney Ng, Kristen A. Severson, Wei Huang, Fred Anderson, Collin M. Stultz
2016	J	`jnl`	Mollack: a web server for the automated creation of conformational ensembles for intrinsically disordered proteins. Bioinform. Zachary Ziegler, Molly Schmidt, Thomas Gurry, Virginia Burger, Collin M. Stultz
2016	—	`conf`	Transferring Knowledge from Text to Predict Disease Onset. MLHC Yun Liu, Collin M. Stultz, John V. Guttag, Kun-Ta Chuang, Fu-Wen Liang, Huey-Jen Su
2016	J	`jnl`	Transferring Knowledge from Text to Predict Disease Onset. CoRR Yun Liu, Kun-Ta Chuang, Fu-Wen Liang, Huey-Jen Su, Collin M. Stultz, John V. Guttag
2012	Misc	`conf`	Efficient Construction of Disordered Protein Ensembles in a Bayesian Framework with Optimal Selection of Conformations. Pacific Symposium on Biocomputing Charles K. Fisher, Orly Ullman, Collin M. Stultz
2010	J	`jnl`	Motif discovery in physiological datasets: A methodology for inferring predictive elements. ACM Trans. Knowl. Discov. Data Zeeshan Syed, Collin M. Stultz, Manolis Kellis, Piotr Indyk, John V. Guttag
2009	J	`jnl`	The multi-copy simultaneous search methodology: a fundamental tool for structure-based drug design. J. Comput. Aided Mol. Des. Christian R. Schubert, Collin M. Stultz
2008	J	`jnl`	The Effect of a ΔK280 Mutation on the Unfolded State of a Microtubule-Binding Repeat in Tau. PLoS Comput. Biol. Austin Huang, Collin M. Stultz
2007	J	`jnl`	Clustering and Symbolic Analysis of Cardiovascular Signals: Discovery and Visualization of Medically Relevant Patterns in Long-Term Data Using Limited Prior Knowledge. EURASIP J. Adv. Signal Process. Zeeshan Syed, John V. Guttag, Collin M. Stultz