Showing 5,261 - 5,280 results of 5,996 for search '((skin OR find) OR (((aina OR anna) OR (peng OR linguo)) OR (ping OR link)))', query time: 0.07s Refine Results
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    Metabolomic characterisation of low-density lipoproteins isolated from iodixanol and KBr-based density gradient ultracentrifugation by Webb, Richard, Lodge, John, Scott, Sophie, Davies, Ian

    Published 2025
    “…Differences were shown in the molecular composition of LDL prepared using SBUC and IGUC; in positive mode ionisation, the PLS-DA model showed reasonable fit and discriminatory power (R2 = 0.63, Q2 = 0.58, accuracy 0.88) and permutation testing was significant (p < 0.001). Conclusions: The findings reveal distinct differences in the small molecule composition of LDL prepared using the two methods, with IGUC exhibiting greater variation. …”
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  19. 5279

    Advancing cyber incident timeline analysis through retrieval-augmented generation and large language models by Loumachi, Fatma Yasmine, Ghanem, Mohamed Chahine, Ferrag, Mohamed Amine

    Published 2025
    “…The proposed framework was tested on synthetic cyber incident events in a controlled environment, with results assessed using DFIR-tailored, context-specific metrics designed to evaluate the framework’s performance, reliability, and robustness, supported by human evaluation to validate the accuracy and reliability of the outcomes. Our findings demonstrate the practical power of LLMs in advancing the automation of cyber-incident timeline analysis, a subfield within DFIR. …”
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  20. 5280

    Incorporation of XAI and deep learning in biomedical imaging: a review by Singh, Sushil Kumar, Virdee, Bal Singh, Aggarwal, Saurabh, Maroju, Abhilash

    Published 2025
    “…Additionally, the review identifies emerging trends and potential future directions in XAI research, offering a structured categorization of techniques based on their suitability for diverse diagnostic tasks. These findings are invaluable for healthcare professionals seeking accurate and reliable diagnostic support, policymakers addressing regulatory and ethical considerations, and AI developers aiming to design systems that balance innovation, safety, and clinical transparency.…”
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