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  1. 281

    DETECTION AND SYSTEMATIZATION OF SIGNS AND MARKERS OF MODIFICATIONS IN MEDIA CONTENT FOR THE DEVELOPMENT OF A METHODOLOGY TO ENHANCING CRITICAL THINKING IN THE ERA OF DEEPFAKES by Ганна Чемерис

    Published 2024-02-01
    “…The paper focuses on creating a comprehensive framework for detecting manipulated content and identifying indicators such as pixelization, unnatural expressions, etc. …”
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  2. 282
  3. 283

    Phenotypic variation of Thenus spp. (Decapoda, Scyllaridae) in the waters of southern Thailand and Malaysia using multivariate morphometric analysis by Ihsan Hani Radzi, Cheng-Ann Chen, Sukree Hajisamae, Kay Khine Soe

    Published 2025-01-01
    “…This study focuses on collecting population information on Thenus orientalis and Thenus indicus from selected sites in southern Thailand and Malaysia to inform sustainable fisheries management about the resources. Twenty-five size-adjusted morphometric measurements were analyzed using canonical discriminant function and dendrogram cluster analyses to examine patterns of phenotypic variation between sites. …”
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  4. 284

    Exploratory integration of near-infrared spectroscopy with clinical data: a machine learning approach for HCV detection in serum samples by Eloy Pérez-Gómez, José Gómez, José Gómez, Jennifer Gonzalo, Sergio Salgüero, Daniel Riado, María Luisa Casas, María Luisa Gutiérrez, Elena Jaime, Enrique Pérez-Martínez, Rafael García-Carretero, Javier Ramos, Conrado Fernández-Rodríguez, Conrado Fernández-Rodríguez, Myriam Catalá, Myriam Catalá, Luca Martino, Óscar Barquero-Pérez

    Published 2025-06-01
    “…Feature importance analysis highlighted specific wavelengths near 1,150 nm, 1,410 nm, and 1,927 nm, associated with water molecular states and liver function biomarkers (GPT, GOT, GGT), reinforcing the biological relevance of this approach.ConclusionsThese findings suggest that integrating NIRS and clinical data through machine learning enhances HCV diagnostic capabilities, offering a scalable and non-invasive alternative for early detection and risk assessment.…”
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  5. 285

    Software with artificial intelligence-derived algorithms for detecting and analysing lung nodules in CT scans: systematic review and economic evaluation by Julia Geppert, Peter Auguste, Asra Asgharzadeh, Hesam Ghiasvand, Mubarak Patel, Anna Brown, Surangi Jayakody, Emma Helm, Dan Todkill, Jason Madan, Chris Stinton, Daniel Gallacher, Sian Taylor-Phillips, Yen-Fu Chen

    Published 2025-05-01
    “…Information required to populate the models included the prevalence of lung nodules, risk of lung cancer with different nodule sizes, sensitivity and specificity for nodule detection, nodule type and size distributions in different population, resource use, costs and utilities. …”
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  6. 286

    Empowering Healthcare: TinyML for Precise Lung Disease Classification by Youssef Abadade, Nabil Benamar, Miloud Bagaa, Habiba Chaoui

    Published 2024-10-01
    “…However, it has limitations, such as a lack of recording functionality, dependence on the expertise and judgment of physicians, and the absence of noise-filtering capabilities. …”
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  7. 287
  8. 288

    Palm-size wireless piezoelectric immune-biosensing system for rapid E. coli O157:H7 detection by Yang Tian, Lisa Kelso, Yiting Xiao, Chaitanya Pallerla, Ramesh Bist, Siavash Mahmoudi, Ziyu Liu, Haizheng Xiong, Jeyam Subbiah, Terry Howell, Dongyi Wang

    Published 2025-01-01
    “…By enabling timely and accurate detection of contaminants, this technology has the potential to significantly impact public health by reducing the incidence of foodborne illnesses, safeguarding environmental resources, and enhancing overall safety and health outcomes.…”
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  9. 289
  10. 290

    Relationship between early neurological function and motor skills in Brazilian preterm infants: a cross-sectional study by Wendy Gabrielle Franca de Sousa, Ana Luiza Righetto Greco, Maja de Medeiros, Alicia Jane Spittle, Cibelle Kayenne Roberto Formiga

    Published 2025-08-01
    “…Thus, monitoring their development is needed for early detection and targeted intervention. This study aimed to assess the correlation between neurological function and motor skills in preterm infants from 2 to 6 months of corrected age after hospital discharge in an outpatient follow-up program. …”
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  15. 295

    LiSA-MobileNetV2: an extremely lightweight deep learning model with Swish activation and attention mechanism for accurate rice disease classification by Yongqi Xu, Dongcheng Li, Changcheng Li, Zheming Yuan, Zhijun Dai

    Published 2025-08-01
    “…LiSA-MobileNetV2 provides a high-accuracy, resource-efficient solution for real-time rice disease detection in smart farming systems.…”
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  16. 296
  17. 297

    GYS-RT-DETR: A Lightweight Citrus Disease Detection Model Based on Integrated Adaptive Pruning and Dynamic Knowledge Distillation by Linlin Yang, Zhonghao Huang, Yi Huangfu, Rui Liu, Xuerui Wang, Zhiwei Pan, Jie Shi

    Published 2025-06-01
    “…Given the serious economic burden that citrus diseases impose on fruit farmers and related industries, achieving rapid and accurate disease detection is particularly crucial. In response to the challenges posed by resource-limited platforms and complex backgrounds, this paper designs and proposes a lightweight method for the identification and localization of citrus diseases based on the RT-DETR-r18 model—GYS-RT-DETR. …”
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  18. 298
  19. 299

    Bio-nanoparticles sensor couple with smartphone digital image colorimetry and dispersive liquid–liquid microextraction for aflatoxin B1 detection by Mahsa Alikord, Nabi Shariatifar, Mammad Saraji, Hedayat Hosseini, Gholamreza Jahed Khaniki, Shahram Shoeibi, Toba Rezazadeh, Mohammad Fazeli

    Published 2025-03-01
    “…Abstract A novel nanobiosensor-based colorimetric method was developed by integrating ZnO nanoparticles functionalized with curcumin, dispersive liquid–liquid microextraction (DLLME), and smartphone digital image colorimetry for the sensitive detection of aflatoxin B1 (AFB1) in baby food samples. …”
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  20. 300

    A Comprehensive Review of Detection Methods for <i>Staphylococcus aureus</i> and Its Enterotoxins in Food: From Traditional to Emerging Technologies by Assia Mairi, Nasir Adam Ibrahim, Takfarinas Idres, Abdelaziz Touati

    Published 2025-06-01
    “…Molecular methods, such as PCR and isothermal amplification, provide high specificity and speed for bacterial and toxin gene detection but cannot confirm functional toxin production. …”
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