Learning more with less data using domain-guided machine learning: the case for health data analytics
type: CreativeWork
description: Made available in DSpace on 2021-03-05T21:38:15Z (GMT). No. of bitstreams: 3 VARATHARAJAH-DISSERTATION-2020.pdf: 17823529 bytes, checksum: 6c1070e8f1e0df625a8309c2990a370f (MD5) LICENSE.txt: 4221 bytes, checksum: addd7522017ee47c1e7f139ef09b27cd (MD5) PROQUEST_LICENSE.txt: 4567 bytes, checksum: c056d1966d17cddcfc4b00a76bec2db5 (MD5) Previous issue date: 2020-12-02
abstract: Made available in DSpace on 2021-03-05T21:38:15Z (GMT). No. of bitstreams: 3 VARATHARAJAH-DISSERTATION-2020.pdf: 17823529 bytes, checksum: 6c1070e8f1e0df625a8309c2990a370f (MD5) LICENSE.txt: 4221 bytes, checksum: addd7522017ee47c1e7f139ef09b27cd (MD5) PROQUEST_LICENSE.txt: 4567 bytes, checksum: c056d1966d17cddcfc4b00a76bec2db5 (MD5) Previous issue date: 2020-12-02
author: Varatharajah, Yogatheesan
language: en
keywords: Machine Learning, Neurology, Artificial Intelligence, Domain-guided, Healthcare, Signal Processing, Interpretability, Intelligence Augmentation
date published: 2021-03-05T21:38:15Z
date modified: 2026-07-22T22:24:50Z
provider: University of Illinois - Urbana-Champaign
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Illinois at Urbana-Champaign

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property ID: Handle
value: http://hdl.handle.net/2142/109413