Best Practices for Heterogenous Health IoT Integration into Electronic Health Records
| dc.contributor.author | DeWitt, Jeffrey | |
| dc.date.accessioned | 2019-07-17T22:44:07Z | |
| dc.date.available | 2019-07-17T22:44:07Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | Health IoT represents an agglomeration of medically-based devices that automate collection, communication, and processing of health data (Da Costa, Pasluosta, Eskofier, Da Silva, & Da Rosa Righi, 2018). This study examines how healthcare institutions can integrate heterogenous data into electronic health records. Key potential benefits are within precision medicine (Prosperi, Min, Bian, & Modave, 2018), patient chronic illnesses (Peng & Goswami, 2018), and advanced patient monitoring inside and outside of hospitals (Rodrigues et al., 2017). | en_US |
| dc.identifier.uri | https://hdl.handle.net/1794/24787 | |
| dc.language.iso | en | en_US |
| dc.publisher | University of Oregon | en_US |
| dc.relation.ispartofseries | AIM Capstone;DeWitt2019 | |
| dc.rights | Creative Commons BY-NC-ND 4.0-US | en_US |
| dc.subject | Health IoT | en_US |
| dc.subject | Wearables | en_US |
| dc.subject | Big Data | en_US |
| dc.subject | Cloud computing | en_US |
| dc.subject | Electronic health record | en_US |
| dc.subject | Smart healthcare | en_US |
| dc.subject | Semantic ontology | en_US |
| dc.subject | Autonomic computing | en_US |
| dc.subject | Cognitive computing | en_US |
| dc.subject | Machine learning | en_US |
| dc.subject | Artificial intelligence | en_US |
| dc.title | Best Practices for Heterogenous Health IoT Integration into Electronic Health Records | en_US |
| dc.type | Terminal Project | en_US |