Predictive analytics and deep learning techniques in electronic medical records : recent advancements and future direction

Belal Alsinglawi, Omar Mubin

Research output: Chapter in Book / Conference PaperConference Paperpeer-review

3 Citations (Scopus)

Abstract

![CDATA[The demands on medical services are increasing rapidly in the global context. Therefore, handling beds availability, identifying and managing the length of stay (LOS) is creating persistent needs for the physicians, nurses, clinicians, hospital management, and caregivers in the public hospital admissions and the private hospital admissions. Health analytics provides unprecedented ways to predict trends, patients’ future outcomes, knowledge discovery, and improving the decision making in the clinical settings. This paper reviews the state-of-the-art machine learning, deep learning techniques and the related work in relation to the length of stay common hospital admissions. Research trends and future direction for the forecasting LOS in medical admissions are discussed in this paper.]]
Original languageEnglish
Title of host publicationWeb, Artificial Intelligence and Network Applications: Proceedings of the Workshops of the 33rd International Conference on Advanced Information Networking and Applications (WAINA-2019), Matsue, Japan, 27-29 March 2019
PublisherSpringer Nature
Pages907-914
Number of pages8
ISBN (Print)9783030150341
DOIs
Publication statusPublished - 2019
EventInternational Conference on Advanced Information Networking and Applications -
Duration: 27 Mar 2019 → …

Publication series

Name
ISSN (Print)2194-5357

Conference

ConferenceInternational Conference on Advanced Information Networking and Applications
Period27/03/19 → …

Keywords

  • artificial intelligence
  • data processing
  • decision making
  • hospitals
  • medical records

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