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An Interactive Machine Learning Approach to Integrating Physician Expertise into Delirium Prediction Model Development.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	An Interactive Machine Learning Approach to Integrating Physician Expertise into Delirium Prediction Model Development./
作者:	Zhang, Yilun.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	71 p.
附註:	Source: Masters Abstracts International, Volume: 83-06.
Contained By:	Masters Abstracts International83-06.
標題:	Industrial engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28770345
ISBN:	9798496554374

An Interactive Machine Learning Approach to Integrating Physician Expertise into Delirium Prediction Model Development.
Zhang, Yilun.

An Interactive Machine Learning Approach to Integrating Physician Expertise into Delirium Prediction Model Development. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 71 p.

Source: Masters Abstracts International, Volume: 83-06.

Thesis (M.A.S.)--University of Toronto (Canada), 2021.

This item must not be sold to any third party vendors.

Delirium is an acute neurocognitive disorder which affects up to half of older hospitalized patients, leading to dementia, longer hospital stays, increased health costs, and death. While delirium can be prevented and treated, it is difficult to identify and predict. Within the GEMINI study, a detailed manual review of medical records has been conducted on nearly 4000 admissions at six hospitals in the Greater Toronto Area, of which approximately 25% have been labeled as having delirium. Using the data collected from this study, we develop machine learning (ML) models with, and without, expert knowledge. By comparison, physician expertise indeed improves delirium status prediction performance and the performance is found to be stable over time. Based on the experimental findings, we further discuss the potential value of using such interactive machine learning (iML) approaches in general healthcare ML applications. Overall, this thesis provides a new perspective on developing delirium prediction models.

ISBN: 9798496554374Subjects--Topical Terms:

526216
Industrial engineering.
Subjects--Index Terms:

Healthcare

An Interactive Machine Learning Approach to Integrating Physician Expertise into Delirium Prediction Model Development.
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