Predictive Analytics and Deep Learning Techniques in Electronic Medical Records: Recent Advancements and Future Direction

  • Belal AlsinglawiEmail author
  • Omar Mubin
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 927)


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.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Western Sydney UniversitySydneyAustralia

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