John V. Guttag
Affiliations: | Massachusetts Institute of Technology, Cambridge, MA, United States |
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"John Guttag"Mean distance: 106866
Cross-listing: Computer Science Tree
Parents
Sign in to add mentor| James Horning | grad student | 1975 | University of Toronto (Physics Tree) | |
| (The Specification and Application to Programming of Abstract Data Types) | ||||
Children
Sign in to add trainee| David Evans | grad student | (Computer Science Tree) | |
| Mandayram Srivas | grad student | 1982 | MIT (Computer Science Tree) |
| Jeannette M. Wing | grad student | 1983 | MIT (Computer Science Tree) |
| Katherine A. Yelick | grad student | 1990 | MIT (Computer Science Tree) |
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Publications
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| Dalca AV, Balakrishnan G, Guttag J, et al. (2019) Unsupervised learning of probabilistic diffeomorphic registration for images and surfaces. Medical Image Analysis. 57: 226-236 |
| Cortés JP, Espinoza VM, Ghassemi M, et al. (2018) Ambulatory assessment of phonotraumatic vocal hyperfunction using glottal airflow measures estimated from neck-surface acceleration. Plos One. 13: e0209017 |
| Oh J, Makar M, Fusco C, et al. (2018) A Generalizable, Data-Driven Approach to Predict Daily Risk of Clostridium difficile Infection at Two Large Academic Health Centers. Infection Control and Hospital Epidemiology. 39: 425-433 |
| Brooks J, Kerr M, Guttag J. (2016) Using machine learning to draw inferences from pass location data in soccer Statistical Analysis and Data Mining: the Asa Data Science Journal. 9: 338-349 |
| Mehta DD, Van Stan JH, Zañartu M, et al. (2015) Using Ambulatory Voice Monitoring to Investigate Common Voice Disorders: Research Update. Frontiers in Bioengineering and Biotechnology. 3: 155 |
| Ghassemi M, Van Stan JH, Mehta DD, et al. (2015) Corrections to "Learning to Detect Vocal Hyperfunction From Ambulatory Neck-Surface Acceleration Features: Initial Results For Vocal Fold Nodules". Ieee Transactions On Bio-Medical Engineering. 62: 2544 |
| Singh A, Nadkarni G, Gottesman O, et al. (2015) Incorporating temporal EHR data in predictive models for risk stratification of renal function deterioration. Journal of Biomedical Informatics. 53: 220-8 |
| Ghassemi M, Van Stan JH, Mehta DD, et al. (2014) Learning to detect vocal hyperfunction from ambulatory neck-surface acceleration features: initial results for vocal fold nodules. Ieee Transactions On Bio-Medical Engineering. 61: 1668-75 |
| Hillman RE, Mehta D, Van Stan JH, et al. (2014) Subglottal ambulatory monitoring of vocal function to improve voice disorder assessment The Journal of the Acoustical Society of America. 136: 2260-2260 |
| Kharbouch A, Shoeb A, Guttag J, et al. (2011) An algorithm for seizure onset detection using intracranial EEG. Epilepsy & Behavior : E&B. 22: S29-35 |