| dc.contributor.advisor | Robert M. Freund. | en_US |
| dc.contributor.author | Verma, Rohil. | en_US |
| dc.contributor.other | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. | en_US |
| dc.date.accessioned | 2021-01-06T18:32:30Z | |
| dc.date.available | 2021-01-06T18:32:30Z | |
| dc.date.copyright | 2020 | en_US |
| dc.date.issued | 2020 | en_US |
| dc.identifier.uri | https://hdl.handle.net/1721.1/129170 | |
| dc.description | Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, September, 2020 | en_US |
| dc.description | Cataloged from student-submitted PDF of thesis. | en_US |
| dc.description | Includes bibliographical references (pages 87-90). | en_US |
| dc.description.abstract | We develop high-performance machine learning automation systems for utilization management that are effective across all specialties. We were motivated by the knowledge that current automation systems for utilization management are rules- based and focused on narrow subsets of healthcare specialties. We develop models that can automate nearly 90% of a utilization management team's workload with less than 1% error. We evaluate these models on both historical data and as part of a live system in industry. The performance and efficacy of our models are consistent across both evaluation domains, demonstrating the generalizability of our work. | en_US |
| dc.description.statementofresponsibility | by Rohil Verma. | en_US |
| dc.format.extent | 90 pages | en_US |
| dc.language.iso | eng | en_US |
| dc.publisher | Massachusetts Institute of Technology | en_US |
| dc.rights | MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided. | en_US |
| dc.rights.uri | http://dspace.mit.edu/handle/1721.1/7582 | en_US |
| dc.subject | Electrical Engineering and Computer Science. | en_US |
| dc.title | A machine learning automation system for utilization management | en_US |
| dc.type | Thesis | en_US |
| dc.description.degree | M. Eng. | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | en_US |
| dc.identifier.oclc | 1227276857 | en_US |
| dc.description.collection | M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science | en_US |
| dspace.imported | 2021-01-06T18:32:29Z | en_US |
| mit.thesis.degree | Master | en_US |
| mit.thesis.department | EECS | en_US |
