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ISSN 0928-7329 (P)
Impact Factor 2023: 1.6
Technology and Health Care is intended to serve as a forum for the presentation of original articles and technical notes, observing rigorous scientific standards. Furthermore, upon invitation, reviews, tutorials, discussion papers and minisymposia are featured.
The following types of contributions and areas are considered:
1. Original articles:
Technology development in medicine: New concepts, procedures and devices associated with the use of technology in medical research and clinical practice are presented to a readership with a widespread background in engineering and/or medicine.
Significance of medical technology and informatics for healthcare: The appropriateness, efficacy and usefulness deriving from the application of engineering methods, devices and informatics in medicine and with respect to public health are discussed.
2. Technical notes:
Short communications on novel technical developments with relevance for clinical medicine.
3. Reviews and tutorials (upon invitation only):
Tutorial and educational articles for persons with a primarily medical background on principles of engineering with particular significance for biomedical applications and vice versa are presented.
4. Minisymposia (upon invitation only):
Under the leadership of a Special Editor, controversial issues relating to healthcare are highlighted and discussed by various authors.
Abstract: The advance of high-performance computing (HPC), high-performance data analytics (HPDA) and AI and their synergetic integration into workflows has revolutionized numerous industries, amongst others the medical and pharmaceutical sectors. In this special section of Technology and Health Care , we delve into the remarkable advancements and potential of HPC, HPDA and AI (together termed HPC+ ) in driving innovation, improving patient outcomes, and accelerating drug discovery. The articles in this issue shed light onto the potential of HPC+ in addressing several critical areas, including medical imaging, personalized medicine, drug discovery, and clinical as well as political decision support.
Keywords: Computer simulation, big data, image processing, computer-assisted diagnosis, drug development, computer-assisted decision making, precision medicine
Abstract: BACKGROUND: To say data is revolutionising the medical sector would be a vast understatement. The amount of medical data available today is unprecedented and has the potential to enable to date unseen forms of healthcare. To process this huge amount of data, an equally huge amount of computing power is required, which cannot be provided by regular desktop computers. These areas can be (and already are) supported by High-Performance-Computing (HPC), High-Performance Data Analytics (HPDA), and AI (together “HPC+ ”). OBJECTIVE: This overview article aims to show state-of-the-art examples of studies supported by the National…Competence Centres (NCCs) in HPC+ within the EuroCC project, employing HPC, HPDA and AI for medical applications. METHOD: The included studies on different applications of HPC in the medical sector were sourced from the National Competence Centres in HPC and compiled into an overview article. Methods include the application of HPC+ for medical image processing, high-performance medical and pharmaceutical data analytics, an application for pediatric dosimetry, and a cloud-based HPC platform to support systemic pulmonary shunting procedures. RESULTS: This article showcases state-of-the-art applications and large-scale data analytics in the medical sector employing HPC+ within surgery, medical image processing in diagnostics, nutritional support of patients in hospitals, treating congenital heart diseases in children, and within basic research. CONCLUSION: HPC+ support scientific fields from research to industrial applications in the medical area, enabling researchers to run faster and more complex calculations, simulations and data analyses for the direct benefit of patients, doctors, clinicians and as an accelerator for medical research.
Keywords: Computer simulation, computational modeling, data analysis, AI (artificial intelligence), medicine, therapeutics, diagnosis
Abstract: BACKGROUND: The necessity of setting up high-resolution models is essential to timely forecast dangerous meteorological phenomena. OBJECTIVE: This study presents a verification of the numerical Weather Research and Forecasting non-hydrostatic Mesoscale Model (WRF NMM) for weather prediction using the High-Performance Computing (HPC) cluster over the complex relief of Montenegro. METHODS: Verification was performed comparing WRF NMM predicted values and measured values for temperature, wind and precipitation for six Montenegrin weather stations in a five-year period using statistical parameters. The difficult task of adjusting the model over the complex Montenegrin terrain is caused by…a rapid altitude change in in the coastal area, numerous karst fields, basins, river valleys and canyons, large areas of artificial lakes on a relatively small terrain. RESULTS: Based on the obtained verification results, the results of the model vary during time of day, the season of the year, the altitude of the station for which the model results were verified, as well as the surrounding relief for them. The results show the best performance in the central region and show deviations for some metrological measures in some periods of the year. CONCLUSION: This study can give recommendations on how to adapt a numerical model to a real situation in order to produce better weather forecast for the public.
Abstract: BACKGROUND: Absorptive capacity is the ability to absorb new knowledge and adopt new technologies. This capacity of an economy is measured through a series of indicators, however, the most important among them are precisely those elements related to the competences required for the adoption of new technologies, as well as their structure. OBJECTIVE: This paper provides an overview of the concepts and systems needed to develop the competencies needed to implement modern technology such as High-Performance Computing (HPC) in Montenegro. METHOD: In this research paper competencies are viewed holistically. This paper will elaborate…the defined competencies related to the HPC technology environment, identified during the implementation of the EuroCC project in Montenegro, but also based on market analyses, combined with the identified indicators of absorption capacity, generally at the national level. RESULT: By identifying the innovative and business potential of representatives of the public, academic and economic sectors, with special reference to small and medium-sized companies and the IT cluster that make up the dominant segments in the structure of the market sample, as generators and accelerators of innovation, smart growth and the digital economy, we got a clear picture regarding the development of necessary competencies within the NCC team but also at the national level. CONCLUSION: There must be a systemic approach and sustainable, dynamic projects and tools for the development of human resources in the development of competences.
Keywords: Competencies, absorption capacity, HPC new technology, knowledge environment
Abstract: Luxembourg’s supercomputer MeluXina is open to cooperation with companies that need to process huge quantities of data. Diem Bui, Solution Engineer at LuxProvide that manages MeluXina, explains how healthtech companies can benefit from supercomputing to develop and implement innovative health technology applications.
Abstract: BACKGROUND: The clinical performance of medical devices is becoming increasingly important for the requirements of modern development processes and the associated regulations. However, the evidence for this performance can often only be obtained very late in the development process via clinical trials or studies. OBJECTIVE: The purpose of the presented work is to show that the simulation of bone-implant systems has advanced in various aspects, including cloud-based execution, Virtual Clinical Trials, and material modeling towards a point where and widespread utilization in healthcare for procedure planning and enhancing practices seems feasible. But this will only hold…true if the virtual cohort data build from clinical Computer Tomography data are collected and analysed with care. METHODS: An overview of the principal steps necessary to perform Finite Element Method based structural mechanical simulations of bone-implant systems based on clinical imaging data is presented. Since these data form the baseline for virtual cohort construction, we present an enhancement method to make them more accurate and reliable. RESULTS: The findings of our work comprise the initial step towards a virtual cohort for the evaluation of proximal femur implants. In addition, results of our proposed enhancement methodology for clinical Computer Tomography data that demonstrate the necessity for the usage of multiple image reconstructions are presented. CONCLUSION: Simulation methodologies and pipelines nowadays are mature and have turnaround times that allow for a day-to-day use. However, small changes in the imaging and the preprocessing of data can have a significant impact on the obtaind results. Consequently, first steps towards virtual clinical trials, like collecting bone samples, are done, but the reliability of the input data remains subject to further research and development.
Keywords: Simulation, bone-implant systems, computed tomography, in silicio, finite element method, virtual clinical trials, high-performance computing