Machine learning and crowdsourcing for digital behavioral phenotyping
Abstract/Contents
- Abstract
- Early childhood is the most potent opportunity to impact long-term health and learning. However, there are major bottlenecks to care, with a massive shortage of clinicians for diagnosis and treatment, disproportionately affecting underserved populations. This thesis centers around developing a streamlined system for continuously phenotyping children with potential developmental delays by leveraging distributed non-expert crowdworkers in conjunction with machine learning algorithms. This work involves collecting diagnostically rich information from children and their parents in a secure and trustworthy manner, curating a reliable and capable crowd workforce for labeling behavioral features, and training behavioral computer vision classifiers for detection of neurodevelopmental concerns
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2022; ©2022 |
| Publication date | 2022; 2022 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Washington, Peter Yigitcan |
|---|---|
| Degree supervisor | Wall, Dennis Paul |
| Thesis advisor | Wall, Dennis Paul |
| Thesis advisor | Altman, Russ |
| Thesis advisor | Liphardt, Jan |
| Degree committee member | Altman, Russ |
| Degree committee member | Liphardt, Jan |
| Associated with | Stanford University, Department of Bioengineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Peter Yigitcan Washington |
|---|---|
| Note | Submitted to the Department of Bioengineering |
| Thesis | Thesis Ph.D. Stanford University 2022 |
| Location | https://purl.stanford.edu/rn871vb3166 |
Access conditions
- Copyright
- © 2022 by Peter Yigitcan Washington
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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