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How can we use data and technology to assist with decision-making in health and healthcare delivery? 
 
A central theme of my research is concerned with developing health informatics and data science tools as data-driven decision support for health and healthcare delivery. I am interested in outcome prediction, process optimization, and health communication. My research is funded by the NIH, AHRQ, and US-DOT. 

Aside from research, as the Informatics Director of Clinical Decision Support at NewYork-Presbyterian Hospital, I also work on the implementation of prediction models into the electronic health record systems.

I am fluent in English, Japanese, and Chinese. I welcome global research collaborations.

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Follow me on LinkedIn and Google Scholar for recent news and updates! ​

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SELECTED RESEARCH PROJECTS

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MACHINE LEARNING ALGORITHM DEVELOPMENT

The application of AI in health requires a deep knowledge about the methodology and the domain. We develop customized algorithms for data-driven clinical decision support.

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PROCESS OPTIMIZATION

The electronic health record captures a wealth of data on clinician decisions and activities. We study these logs to propose optimization in the clinical workflow.

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SPECIAL (SUPPORTING PREGNANCY CARE USING ARTIFICIAL INTELLIGENCE)

Maternal health remains an understudied area in Health Informatics. We aim to improve care process and outcomes using AI.

Development and validation of a machine learning algorithm for predicting the risk of postpartum depression among pregnant women

+ see the white paper for model description, and docker container instruction for downloading the codes:

docker pull ichiyoz/ppd

GET IN TOUCH

I am looking for a research assistant to join my team!


Weill Cornell Medicine, Department of Healthcare Policy and Research, Division of Health Informatics

425 E 61st St
New York, New York County 10065
USA

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