Predicting risk of hospital readmission for comorbidity patients through a novel deep learning framework

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Dashtban, M. and Li, W. (V.) orcid id iconORCID: https://orcid.org/0000-0003-2878-3185 (2020) Predicting risk of hospital readmission for comorbidity patients through a novel deep learning framework. In: 53rd Hawaii International Conference on System Sciences, 7-10 Jan 2020, Maui, Hawaii.

Item Type Conference or Workshop Item (Paper)
URI https://reading-clone.eprints-hosting.org/id/eprint/86410
Refereed Yes
Divisions Interdisciplinary centres and themes > Health Innovation Partnership (HIP)
Henley Business School > Digitalisation, Marketing and Entrepreneurship
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[thumbnail of Open Access]
Preview
Text (Open Access) - Published Version
· Available under License Creative Commons Attribution Non-commercial No Derivatives.
· Please see our End User Agreement before downloading.
| Preview
[thumbnail of paper_1071_final (1).pdf]
Text - Accepted Version
· Restricted to Repository staff only
Restricted to Repository staff only
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Please see our End User Agreement.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

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