418 research outputs found
sj-xlsx-1-dhj-10.1177_20552076221074122 - Supplemental material for Magnetic resonance image-based brain tumour segmentation methods: A systematic review
No full textSupplemental material, sj-xlsx-1-dhj-10.1177_20552076221074122 for Magnetic resonance image-based brain tumour segmentation methods: A systematic review by Jayendra M Bhalodiya, Sarah N Lim Choi Keung and Theodoros N Arvanitis in Digital Health</p
Modelling UK sub-sector industrial energy demand
No full textThe importance of considering homogenous economic agents when estimating energy demand functions is recognized in the literature, but so far data availability problems have explained the prevalence of empirical analyses only at an aggregate level. Motivated by the goal of developing the new industrial module to be adopted by the UK government Department of Business, Energy and Industrial Strategy (BEIS) for their econometric Energy Demand Model, we propose the first cointegration analysis that provides evidence on energy demand elasticities with respect to economic activity and energy price at a disaggregated industrial level. While the average of our estimates are comparable to those of the existing literature on the industrial sector as a whole, we find that there is considerable heterogeneity in relation to the long-run impact of economic activity and energy price on energy consumption, as well as to the speed with which firms re-adjust their equilibrium demand of energy in response to economic shocks. Finally, we learn that long-run disequilibria are tackled through altering the level of energy consumption rather than economic activity, a conclusion that has important implications for policy analysis
sj-docx-1-dhj-10.1177_20552076221143236 - Supplemental material for Effect of mobile health interventions in increasing utilization of Maternal and Child Health care services in developing countries: A scoping review
No full textSupplemental material, sj-docx-1-dhj-10.1177_20552076221143236 for Effect of mobile health interventions in increasing utilization of Maternal and Child Health care services in developing countries: A scoping review by Ramachandran Venkataramanan, S.V. Subramanian, Mohannad Alajlani and Theodoros N Arvanitis in Digital Health</p
sj-docx-3-dhj-10.1177_20552076231222100 - Supplemental material for “It depends on the people!” – A qualitative analysis of contextual factors, prior to the implementation of digital health innovations for chronic condition management, in a German integrated care network
No full textSupplemental material, sj-docx-3-dhj-10.1177_20552076231222100 for “It depends on the people!” – A qualitative analysis of contextual factors, prior to the implementation of digital health innovations for chronic condition management, in a German integrated care network by Clemens Moll, Fritz Arndt, Theodoros N. Arvanitis, Nerea Gonzàlez, Oliver Groene, Ana Ortega-Gil, Dolores Verdoy, Janika Bloemeke and on behalf of the ADLIFE consortium in DIGITAL HEALTH</p
sj-docx-1-dhj-10.1177_20552076231222100 - Supplemental material for “It depends on the people!” – A qualitative analysis of contextual factors, prior to the implementation of digital health innovations for chronic condition management, in a German integrated care network
No full textSupplemental material, sj-docx-1-dhj-10.1177_20552076231222100 for “It depends on the people!” – A qualitative analysis of contextual factors, prior to the implementation of digital health innovations for chronic condition management, in a German integrated care network by Clemens Moll, Fritz Arndt, Theodoros N. Arvanitis, Nerea Gonzàlez, Oliver Groene, Ana Ortega-Gil, Dolores Verdoy, Janika Bloemeke and on behalf of the ADLIFE consortium in DIGITAL HEALTH</p
sj-docx-2-dhj-10.1177_20552076231222100 - Supplemental material for “It depends on the people!” – A qualitative analysis of contextual factors, prior to the implementation of digital health innovations for chronic condition management, in a German integrated care network
No full textSupplemental material, sj-docx-2-dhj-10.1177_20552076231222100 for “It depends on the people!” – A qualitative analysis of contextual factors, prior to the implementation of digital health innovations for chronic condition management, in a German integrated care network by Clemens Moll, Fritz Arndt, Theodoros N. Arvanitis, Nerea Gonzàlez, Oliver Groene, Ana Ortega-Gil, Dolores Verdoy, Janika Bloemeke and on behalf of the ADLIFE consortium in DIGITAL HEALTH</p
sj-docx-4-dhj-10.1177_20552076231222100 - Supplemental material for “It depends on the people!” – A qualitative analysis of contextual factors, prior to the implementation of digital health innovations for chronic condition management, in a German integrated care network
No full textSupplemental material, sj-docx-4-dhj-10.1177_20552076231222100 for “It depends on the people!” – A qualitative analysis of contextual factors, prior to the implementation of digital health innovations for chronic condition management, in a German integrated care network by Clemens Moll, Fritz Arndt, Theodoros N. Arvanitis, Nerea Gonzàlez, Oliver Groene, Ana Ortega-Gil, Dolores Verdoy, Janika Bloemeke and on behalf of the ADLIFE consortium in DIGITAL HEALTH</p
Transforming Healthcare:The Role of Artificial Intelligence
Full text linkThe integration of artificial intelligence (AI) into healthcare is revolutionising the industry by enhancing diagnostic accuracy, personalising treatment strategies, and improving administrative efficiency. This study aims to evaluate the impact of AI interventions on health outcomes across various medical applications. A scoping review was conducted using relevant search terms, focusing exclusively on interventional studies measuring AI’s effectiveness on health outcomes. The review analysed 30 clinical trials, including behavioural interventions, stroke rehabilitation, sepsis prediction, dental caries, and venous thromboembolism. The findings indicate that AI significantly improves adherence to healthy behaviours and enhances engagement in self-monitoring activities, has effective predictive capabilities, particularly in sepsis risk assessment, and demonstrates high accuracy in melanoma detection. However, AI-driven clinical decision support systems did not increase prophylaxis rates for venous thromboembolism or significantly improve motor function, cognition, or quality of life in Parkinson's disease patients. In summary, this review highlights the substantial potential of AI across various healthcare domains. The evidence suggests that AI improves adherence to interventions, enhances healthcare delivery efficiency, facilitates effective disease management, and increases diagnostic accuracy. Continued exploration of AI applications in healthcare is crucial for optimising patient outcomes and addressing implementation challenges within clinical practice.</p
Virtual reality in medicine
No full textThis chapter explores the technological quest of virtual reality within the field of medicine. Although the author does not intend to provide an exhaustive review of the various health informatics applications of VR over the past 15 years of its development, he presents some of the major technological breakthroughs and their impact in the provision of healthcare services to the point-of-need (i.e., the patient)
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