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http://dx.doi.org/10.1016/j.lanepe.2024.101164 | DOI Listing |
Healthcare (Basel)
December 2024
Centre for Digital Transformation, School of Computing and Information Technology, University of Wollongong, Wollongong, NSW 2522, Australia.
Background: Traditional methods for analysing surgical processes often fall short in capturing the intricate interconnectedness between clinical procedures, their execution sequences, and associated resources such as hospital infrastructure, staff, and protocols.
Aim: This study addresses this gap by developing an ontology for appendicectomy, a computational model that comprehensively represents appendicectomy processes and their resource dependencies to support informed decision making and optimise appendicectomy healthcare delivery.
Methods: The ontology was developed using the NeON methodology, drawing knowledge from existing ontologies, scholarly literature, and de-identified patient data from local hospitals.
Big Data
January 2025
Department of Engineering Management, University of Antwerp, Antwerp, Belgium.
Our online lives generate a wealth of behavioral records--which are stored and leveraged by technology platforms. These data can be used to create value for users by personalizing services. At the same time, however, it also poses a threat to people's privacy by offering a highly intimate window into their private traits (e.
View Article and Find Full Text PDFNPJ Digit Med
January 2025
January AI, Menlo Park, CA, USA.
This retrospective cohort study evaluates the impact of an AI-supported continuous glucose monitoring (CGM) mobile app ("January V2") on glycemic control and weight management in 944 users, including healthy individuals and those with prediabetes or type 2 diabetes (T2D). The app, leveraging AI to personalize feedback, tracked users' food intake, activity, and glucose responses over 14 days. Significant improvements in time in range (TIR) were observed, particularly in users with lower baseline TIR.
View Article and Find Full Text PDFSci Rep
January 2025
School of Computer, Heze University, No.2269, Daxue Road, Heze, 274015, Shandong, China.
A switching active disturbance rejection control (SADRC) strategy was proposed to solve the composite disturbance challenge arising from gap, LuGre friction, hydraulic spring force, and external load disturbance in the double closed-loop digital hydraulic cylinder position control system. Firstly, leveraging the established mathematical model of the double closed-loop digital hydraulic cylinder, the high-order state equation was derived. Subsequently, the high-order double closed-loop digital hydraulic cylinder control system was transformed into a second-order integral series control system using ADRC strategy.
View Article and Find Full Text PDFInt J Med Inform
December 2024
Department of Health Science and Technology, Aalborg University, Selma Lagerløfs Vej 249, 9260 Gistrup, Denmark; Data Science, Novo Nordisk A/S, Søborg, Denmark. Electronic address:
Background And Aim: The progressive nature of type 2 diabetes often, in time, necessitates basal insulin therapy to achieve glycemic targets. However, despite standardized titration algorithms, many people remain poorly controlled after initiating insulin therapy, leading to suboptimal glycemic control and complications. Both healthcare professionals and people with type 2 diabetes have expressed the need for novel tools to aid in this process.
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