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ORCIDSantiago Romero-Brufau
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2020 – today
- 2024
[j12]Mukund Poddar, Jayson S. Marwaha
, William Yuan, Santiago Romero-Brufau, Gabriel A. Brat:
An operational guide to translational clinical machine learning in academic medical centers. npj Digit. Medicine 7(1) (2024)- 2023
- [c7]Belén Otero-Carrasco, Santiago Romero-Brufau, Andrea Álvarez Pérez, Adrián Ayuso Muñoz, Lucía Prieto Santamaría, Juan Pedro Caraça-Valente Hernández, Alejandro Rodríguez González:
Orphan Drugs and Rare Diseases: Unveiling Biological Patterns through Drug Repurposing. CBMS 2023: 185-191 - 2022
- [j11]Erik T. Rosenstrom, Sareh Meshkinfam, Julie Simmons Ivy, Shadi Hassani Goodarzi, Muge Capan, Jeanne Huddleston, Santiago Romero-Brufau:
Optimizing the First Response to Sepsis: An Electronic Health Record-Based Markov Decision Process Model. Decis. Anal. 19(4): 265-296 (2022) - [j10]Raphaëlle Toubiana, Millie Macdonald, Sivananda Rajananda, Tale Lokvenec, Thomas C. Kingsley, Santiago Romero-Brufau:
Blockchain for Electronic Vaccine Certificates: More Cons Than Pros? Frontiers Big Data 5 (2022) - [j9]Young J. Juhn, Euijung Ryu, Chung-Il Wi, Katherine S. King, Momin M. Malik, Santiago Romero-Brufau, Chunhua Weng, Sunghwan Sohn, Richard R. Sharp, John D. Halamka:
Assessing socioeconomic bias in machine learning algorithms in health care: a case study of the HOUSES index. J. Am. Medical Informatics Assoc. 29(7): 1142-1151 (2022) - [c6]Santiago Romero-Brufau, Adam Goulson, Gayla Poling, Devin McCaslin, Scott Eggers, Colin Driscoll, Kalyan S. Pasupathy, Jeffrey Staab:
Long-term accuracy of a hybrid model to automate triage for patients with dizziness. AMIA 2022 - 2021
- [j8]Santiago Romero-Brufau, Daniel Whitford, Matthew G. Johnson, Joel Hickman, Bruce W. Morlan, Terry M. Therneau, James M. Naessens, Jeanne M. Huddleston:
Using machine learning to improve the accuracy of patient deterioration predictions: Mayo Clinic Early Warning Score (MC-EWS). J. Am. Medical Informatics Assoc. 28(6): 1207-1215 (2021) - [j7]Kexin Huang, Tamryn F. Gray, Santiago Romero-Brufau, James A. Tulsky, Charlotta Lindvall:
Using nursing notes to improve clinical outcome prediction in intensive care patients: A retrospective cohort study. J. Am. Medical Informatics Assoc. 28(8): 1660-1666 (2021) - [j6]Alexander J. Ryu, Santiago Romero-Brufau, Narges Shahraki, Jiawei Zhang, Ray Qian, Thomas C. Kingsley:
Practical development and operationalization of a 12-hour hospital census prediction algorithm. J. Am. Medical Informatics Assoc. 28(9): 1977-1981 (2021) - [c5]Ayush Chopra, Ramesh Raskar, Jayakumar Subramanian, Balaji Krishnamurthy, Esma Senturk Gel, Santiago Romero-Brufau, Kalyan S. Pasupathy, Thomas C. Kingsley:
DeepABM: Scalable and Efficient Agent-Based Simulations Via Geometric Learning Frameworks - a Case Study For Covid-19 Spread and Interventions. WSC 2021: 1-12 - [i1]Ayush Chopra, Esma Senturk Gel, Jayakumar Subramanian, Balaji Krishnamurthy, Santiago Romero-Brufau, Kalyan S. Pasupathy, Thomas C. Kingsley, Ramesh Raskar:
DeepABM: Scalable, efficient and differentiable agent-based simulations via graph neural networks. CoRR abs/2110.04421 (2021) - 2020
- [j5]Santiago Romero-Brufau, Kirk D. Wyatt, Patricia Boyum, Mindy Mickelson, Matthew Moore, Cheristi Cognetta-Rieke:
Implementation of Artificial Intelligence-Based Clinical Decision Support to Reduce Hospital Readmissions at a Regional Hospital. Appl. Clin. Inform. 11(04): 570-577 (2020) - [j4]Santiago Romero-Brufau, Kirk D. Wyatt, Patricia Boyum, Mindy Mickelson, Matthew Moore, Cheristi Cognetta-Rieke:
A lesson in implementation: A pre-post study of providers' experience with artificial intelligence-based clinical decision support. Int. J. Medical Informatics 137: 104072 (2020) - [j3]Santiago Romero-Brufau, Kirk D. Wyatt, Patricia Boyum, Mindy Mickelson, Matthew Moore, Cheristi Cognetta-Rieke:
What's in a name? A comparison of attitudes towards artificial intelligence (AI) versus augmented human intelligence (AHI). BMC Medical Informatics Decis. Mak. 20(1): 167 (2020)
2010 – 2019
- 2019
- [j2]Joseph Agor, Osman Y. Özaltin, Julie S. Ivy, Muge Capan, Ryan Arnold, Santiago Romero-Brufau:
The value of missing information in severity of illness score development. J. Biomed. Informatics 97 (2019) - 2018
- [c4]Santiago Romero-Brufau, Kim Gaines, Matthew G. Johnson, Joel Hickman, Terry M. Therneau, Jeanne Huddleston:
The Mayo Clinic Early Warning Score is superior to MEWS, and nursing pattern recognition can improve its accuracy further. AMIA 2018 - [c3]Santiago Romero-Brufau, Jordan Kautz, Kim Gaines, Curt Storlie, Matthew G. Johnson, Joel Hickman, Jeanne Huddleston:
Use of an early warning system with gradual alerting reduces time to therapy in acute inpatient deterioration. AMIA 2018 - [c2]Santiago Romero-Brufau, Petro M. Kostandy, Kayse Maass Lee, Phichet Wutthisirisart, Mustafa Y. Sir, Brian J. Bartholmai, Mickael Stuve, Kalyan S. Pasupathy:
Development of data integration and visualization tools for the Department of Radiology to display operational and strategic metrics. AMIA 2018 - 2016
- [j1]Patricia Kipnis, Benjamin J. Turk, David A. Wulf, Juan Carlos LaGuardia, Vincent X. Liu, Matthew M. Churpek, Santiago Romero-Brufau, Gabriel J. Escobar:
Development and validation of an electronic medical record-based alert score for detection of inpatient deterioration outside the ICU. J. Biomed. Informatics 64: 10-19 (2016) - 2014
- [c1]Aarti Sathyanarayana, Jyotishman Pathak, Rozalina G. McCoy, Santiago Romero-Brufau, Maryam Panaziahar, Jaideep Srivastava:
Clinical Decision Making: A Framework for Predicting Rx Response. ICDM Workshops 2014: 1185-1188
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