| LDR | | 00000nam u2200205 4500 |
| 001 | | 000000434660 |
| 005 | | 20200226165243 |
| 008 | | 200131s2019 ||||||||||||||||| ||eng d |
| 020 | |
▼a 9781687955913 |
| 035 | |
▼a (MiAaPQ)AAI22621827 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
| 082 | 0 |
▼a 004 |
| 100 | 1 |
▼a de Greef, Lilian. |
| 245 | 10 |
▼a Using Consumer Devices to Monitor Acute Medical Conditions for Infants. |
| 260 | |
▼a [S.l.]:
▼b University of Washington.,
▼c 2019. |
| 260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2019. |
| 300 | |
▼a 166 p. |
| 500 | |
▼a Source: Dissertations Abstracts International, Volume: 81-05, Section: B. |
| 500 | |
▼a Advisor: Patel, Shwetak N. |
| 502 | 1 |
▼a Thesis (Ph.D.)--University of Washington, 2019. |
| 506 | |
▼a This item must not be sold to any third party vendors. |
| 506 | |
▼a This item must not be added to any third party search indexes. |
| 520 | |
▼a Acute medical conditions need immediate attention, but early detection can require professional experience and specialized equipment that are unavailable at home. Consequently, babies with such conditions risk suffering damage from late interventions. We can leverage the world's increasingly ubiquitous devices to improve the accessibility of health care outside the hospital through machine learning and integrating a human-centered approach at every step of the process. This dissertation examines this approach through three projects: a smartphone-based system to screen newborns for dangerous levels of jaundice, an exploration on how machine learning can help an existing system better monitor infants with single ventricle heart disease, and a reflection on the methods and insights from working in this space to inform future work. |
| 590 | |
▼a School code: 0250. |
| 650 | 4 |
▼a Computer science. |
| 690 | |
▼a 0984 |
| 710 | 20 |
▼a University of Washington.
▼b Computer Science and Engineering. |
| 773 | 0 |
▼t Dissertations Abstracts International
▼g 81-05B. |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0250 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2019 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15493846
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
| 980 | |
▼a 202002
▼f 2020 |
| 990 | |
▼a ***1008102 |
| 991 | |
▼a E-BOOK |