TY - GEN
T1 - Predictive analytics and deep learning techniques in electronic medical records : recent advancements and future direction
AU - Alsinglawi, Belal
AU - Mubin, Omar
PY - 2019
Y1 - 2019
N2 - ![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.]]
AB - ![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.]]
KW - artificial intelligence
KW - data processing
KW - decision making
KW - hospitals
KW - medical records
UR - http://handle.westernsydney.edu.au:8081/1959.7/uws:51783
UR - https://ebookcentral.proquest.com/lib/uwsau/reader.action?docID=5730784&ppg=954
U2 - 10.1007/978-3-030-15035-8_89
DO - 10.1007/978-3-030-15035-8_89
M3 - Conference Paper
SN - 9783030150341
SP - 907
EP - 914
BT - Web, 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
PB - Springer Nature
T2 - International Conference on Advanced Information Networking and Applications
Y2 - 27 March 2019
ER -