Development and deployment of machine learning in medicine
Abstract/Contents
- Abstract
- Recent advances in machine learning have enabled important applications in medicine, where many critical tasks are tedious and time-consuming for clinicians to perform. This dissertation presents work on using machine learning for cardiology, pathology, and RNA sequencing. This dissertation begins with several applications of machine learning in cardiology, focusing on echocardiograms, or ultrasounds of the heart. Conventional assessment of echocardiograms requires tedious annotation by a human expert. First, I introduce EchoNet-Dynamic, an algorithm for assessing cardiac function from echocardiograms. EchoNet-Dynamic is then integrated into a clinical system and evaluated with a blinded randomized clinical trial. Extensions of the algorithm to pediatric patients and emergency department point-of-care echocardiograms are then presented. This dissertation then presents work applying machine learning to pathology and RNA sequencing. First, I present in silico-IHC, which predicts immunohistochemical stains from commonly available histochemically-stained tissue samples. Next, I present ST-Net, which combines RNA sequencing and pathology by estimating spatial transcriptomics measurements from microscopy images. Finally, I present CloudPred, which predicts patient phenotypes from single-cell RNA sequencing data.
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 | 2023; ©2023 |
| Publication date | 2023; 2023 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | He, Bryan Dawei |
|---|---|
| Degree supervisor | Ermon, Stefano |
| Degree supervisor | Zou, James |
| Thesis advisor | Ermon, Stefano |
| Thesis advisor | Zou, James |
| Thesis advisor | Kundaje, Anshul, 1980- |
| Degree committee member | Kundaje, Anshul, 1980- |
| Associated with | Stanford University, School of Engineering |
| Associated with | Stanford University, Computer Science Department |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Bryan He. |
|---|---|
| Note | Submitted to the Computer Science Department. |
| Thesis | Thesis Ph.D. Stanford University 2023. |
| Location | https://purl.stanford.edu/mq390cr0348 |
Access conditions
- Copyright
- © 2023 by Bryan Dawei He
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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