Medicine - Conference Items

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    Business continuity management of critical infrastructures from the cybersecurity perspective
    (IEEE, 2024-07-08) Savolainen, Timo; McCarthy, Nora; Neville, Karen; Ruoslahti, Harri; Horizon 2020
    In today's society, nearly all processes are connected to IT systems, which means that there is a universal need to investigate how critical infrastructures' resilience can be improved from a cybersecurity perspective. The purpose of this non-systematic literature overview is to explore how business continuity management (BCM) can be improved from a cybersecurity perspective. It investigates different approaches to business continuity management (BCM), and addresses challenges to the resilience of critical infrastructures by looking at business continuity management, concentrating on cybersecurity and artificial intelligence (AI) from a human factor perspective. BCM systems can be very complex and time-consuming and approaches to BCM differ. However, they all have in common the objective of identifying threats and, based on these, offer solutions that ensure the continued operation of critical processes of the organization in terms of maintaining business continuity and resilience. While artificial intelligence (AI) can be used to make the process more efficient, the importance of addressing human factors is critical to BCM. This paper proposes a new practical BCM resilience framework that adds in a core phase of ‘learn and adapt’, currently lacking from existing models, thus recognizing the importance of training and education in human factors.
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    Development and evaluation of online approaches for improved kinaesthetic learning in science
    (Universitat Politecnica de Valencia, 2021) Scanlan, Anna M.; Kennedy, Declan; McCarthy, Tommie V.
    Kinaesthetic learning is expressed when physical actions are used to connect concept development to reality, for example through model building, trial and error practice, or role-play interactions. Learning through a kinaesthetic modality is highly effective and complementary to other learning modalities. Recent advances in gamification for education have increased access to science simulations and learning online. However, the transfer of offline kinaesthetic techniques to online learning remains under-researched and poorly implemented on affordable, scalable platforms. Here we describe an accessible approach for educators on how to incorporate online kinaesthetic aspects into lessons through use of a scalable and affordable framework developed called the ‘Kinaesthetic Learning System’ (KLS). This framework should be of particular use for learning complex molecular life science topics but can be adapted and modified independently by the educator to address different knowledge levels and for expansion to other disciplines.
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    Sparse-denoising methods for extracting desaturation transients in cerebral oxygenation signals of preterm Infants
    (IEEE, 2021-11) Ashoori, Minoo; Dempsey, Eugene M.; McDonald, Fiona B.; O'Toole, John M.; Science Foundation Ireland
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    Non-invasive multimodal spectroscopic diagnosis for early-stage oral cancer
    (Optica Publishing Group, 2023) Maryam, Siddra; Ghauri, Daniyal; Sekar, Sanathana Konugolu Venkata; Fahy, Edward; Saito Nogueira, Marcelo; Lu, Huihui; Beffara, Flavien; Humbert, Georges; Burke, Ray; Feeley, Linda; Sheahan, Patrick; Ni Riordain, Richeal; Andersson-Engels, Stefan; Wei Kho, Kiang; Gautam, Rekha; 2023
    This study aims to develop a multimodal scheme for diagnosing oral cancer non-invasively in its early stages and to assess the performance of an integrated diagnostic platform comprising of Raman and diffuse reflectance spectroscopy systems.
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    Multi-configuration Raman spectrometer for early stage diagnosis of oral cancer
    (Society of Photo-Optical Instrumentation Engineers (SPIE), 2022-03-02) Maryam, Siddra; Saito Nogueira, Marcelo; Krishna Moorthy, Shree; Sekar, Sanathana Konugolu Venkata ; Lu, Huihui; Gautam, Rekha; Burke, Ray; Andersson-Engels, Stefan; Ni Riordain, Richeal; Sheahan, Patrick; Huang, Zhiwei; Science Foundation Ireland
    Oral Squamous Cell carcinoma (OSCC) is one of the most common and aggressive oral malignancies. Despite all significant advances in medicine, five-year survival rate is still 40%-60%. Diagnosis in early stages is critical as it can improve the survival rate and the quality of life after treatment. This study aims to develop a strategy for diagnosing oral cancer non-invasively in the early stages and to provide better surgical guidance by differentiating healthy and tumor tissues by using Raman spectroscopy. For this purpose, a multimodal Raman system is developed to detect oral cancer biomarkers in patient’s saliva specimen and to study different tissue types in oral cavity with Raman spectroscopy. The developed system is quite compact, easy to use and portable. It can be easily modified for in vivo and ex vivo analysis and can work in both reflection and transmission mode in case of ex vivo measurements. This paper compares the surface enhancement and background spectra from different plasmonic nanoparticles. Lastly, bovine serum albumin (BSA) and uric acid were used as model analytes to at physiologically relevant concentrations to test the performance of the system.