Online evolutionary neural architecture search for multivariate non-stationary time series forecasting
Time series forecasting (TSF) is one of the most important tasks in data science. TSF models
are usually pre-trained with historical data and then applied on future unseen datapoints …
are usually pre-trained with historical data and then applied on future unseen datapoints …
[HTML][HTML] A comprehensive and integrated hospital decision support system for efficient and effective healthcare services delivery using discrete event simulation
The difficulty that hospital management has been experiencing over the past decade in
balancing demand and capacity needs is unprecedented in the United Kingdom. Due to a …
balancing demand and capacity needs is unprecedented in the United Kingdom. Due to a …
Daily surgery caseload prediction: towards improving operating theatre efficiency
Background In many hospitals, operating theatres are not used to their full potential due to
the dynamic nature of demand and the complexity of theatre scheduling. Theatre …
the dynamic nature of demand and the complexity of theatre scheduling. Theatre …
A hybrid analytical model for an entire hospital resource optimisation
Given the escalating healthcare costs around the world (more than 10% of the world's GDP)
and increasing demand hospitals are under constant scrutiny in terms of managing services …
and increasing demand hospitals are under constant scrutiny in terms of managing services …
[HTML][HTML] Google trends as a tool for evaluating public interest in total knee arthroplasty and total hip arthroplasty
SA Cohen, LE Cohen, JD Tijerina, G Bouz… - Journal of Clinical …, 2021 - ncbi.nlm.nih.gov
Methods: GT data were compiled for ten search terms related to TKA and ten search terms
related to THA from January 2009 to December 2017. Annual case volumes for TKA/THA …
related to THA from January 2009 to December 2017. Annual case volumes for TKA/THA …
Child opportunity index disparities in pediatric surgical encounters during the coronavirus 2019 pandemic
Objective Surgical encounters decreased during the coronavirus disease (COVID-19)
pandemic and may have been deferred more in children with impeded health care access …
pandemic and may have been deferred more in children with impeded health care access …
Hybrid machine learning models for forecasting surgical case volumes at a hospital
A Aravazhi - AI, 2021 - mdpi.com
Recent developments in machine learning and deep learning have led to the use of multiple
algorithms to make better predictions. Surgical units in hospitals allocate their resources for …
algorithms to make better predictions. Surgical units in hospitals allocate their resources for …
Analysis of exponential smoothing forecasting model of medical cases for resource allocation recommender system
Forecasting the number of incidences of medical cases is important in planning institutional
health program strategies to draft intervention and allocate resources. The utilization of …
health program strategies to draft intervention and allocate resources. The utilization of …
ONE-NAS: an online neuroevolution based neural architecture search for time series forecasting
Time series forecasting (TSF) is one of the most important tasks in data science, as accurate
time series (TS) predictions can drive and advance a wide variety of domains including …
time series (TS) predictions can drive and advance a wide variety of domains including …
ECP: Error-Aware, Cost-Effective and Proactive Network Slicing Framework
Recent advancements in Software Defined Networks (SDN), Open Radio Access Network
(O-RAN), and 5G technology have significantly expanded the capabilities of wireless …
(O-RAN), and 5G technology have significantly expanded the capabilities of wireless …