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Automated retinal imaging and trend analysis – a tool for health monitoring
| dc.contributor.author | Roesch, Karin | |
| dc.contributor.author | Swedish, Tristan | |
| dc.contributor.author | Raskar, Ramesh | |
| dc.date.accessioned | 2021-10-27T20:29:00Z | |
| dc.date.available | 2021-10-27T20:29:00Z | |
| dc.date.issued | 2017 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/135722 | |
| dc.description.abstract | © 2017 Roesch et al. Most current diagnostic devices are expensive, require trained specialists to operate and gather static images with sparse data points. This leads to preventable diseases going undetected until late stage, resulting in greatly narrowed treatment options. This is especially true for retinal imaging. Future solutions are low cost, portable, self-administered by the patient, and capable of providing multiple data points, population analysis, and trending. This enables preventative interventions through mass accessibility, constant monitoring, and predictive modeling. | |
| dc.language.iso | en | |
| dc.publisher | Informa UK Limited | |
| dc.relation.isversionof | 10.2147/OPTH.S116265 | |
| dc.rights | Creative Commons Attribution Noncommercial 3.0 unported license | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc/3.0/ | |
| dc.source | Dove Press | |
| dc.title | Automated retinal imaging and trend analysis – a tool for health monitoring | |
| dc.type | Article | |
| dc.relation.journal | Clinical Ophthalmology | |
| dc.eprint.version | Final published version | |
| dc.type.uri | http://purl.org/eprint/type/JournalArticle | |
| eprint.status | http://purl.org/eprint/status/PeerReviewed | |
| dc.date.updated | 2019-08-02T12:46:07Z | |
| dspace.orderedauthors | Roesch, K; Swedish, T; Raskar, R | |
| dspace.date.submission | 2019-08-02T12:46:08Z | |
| mit.journal.volume | Volume 11 | |
| mit.metadata.status | Authority Work and Publication Information Needed |
