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Showing 1,661 - 1,680 results of 1,810 for search '((( resource OR sources) detection functions ) OR ( sources detection functions ))', query time: 0.36s Refine Results
  1. 1661

    Acoustic Features for Identifying Suicide Risk in Crisis Hotline Callers: Machine Learning Approach by Zhengyuan Su, Huadong Jiang, Ying Yang, Xiangqing Hou, Yanli Su, Li Yang

    Published 2025-04-01
    “…Basic acoustic features (eg, Mel Frequency Cepstral Coefficients, formant frequencies, jitter, shimmer) and high-level statistical function (HSF) features (using OpenSMILE [Open-Source Speech and Music Interpretation by Large-Space Extraction] with the ComParE 2016 configuration) were extracted. …”
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  2. 1662

    Estimating the mass of tephra accumulated on roads to best manage the impact of volcanic eruptions: the example of Mt Etna, Italy by L. Mereu, L. Mereu, M. Stocchi, M. Stocchi, A. Garcia, M. Prestifilippo, L. Sandri, C. Bonadonna, S. Scollo

    Published 2025-06-01
    “…First, we analysed a sequence of 39 short-lasting and intense lava fountains detected by the X-band weather radar, applying a volcanic ash radar retrieval approach that permits us to compute the main eruption source parameters (ESPs), such MER, <span class="inline-formula"><i>H</i><sub>TP</sub></span>, and GSD. …”
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  3. 1663

    LIFE CYCLE ASSESSMENT IN HEALTHCARE SYSTEM OPTIMIZATION. INTRODUCTION by V. Sarancha, K. Vitale, S. Oreskovic, V. Sulyma

    Published 2015-03-01
    “…Various factors and parameters that may influence effectiveness of different sectors in healthcare system are detected. Performance optimization of detected parameters could lead to better system functioning, higher patient safety, economic sustainability and reduce resources consumption.…”
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  4. 1664

    Proteomic analysis of plasma unravels dynamic pathways and potential biomarkers indicating disease stages following Mtb infection by Zonglei Zhou, Jie Tian, Yuying He, Haiyan Xiong, Weibing Wang

    Published 2025-08-01
    “…ABSTRACT Tuberculosis (TB) stages depend greatly on the interaction between Mycobacterium tuberculosis (Mtb) and the host response. As a non-negligible source of active tuberculosis (ATB), individuals with latent Mtb infection (LTBI) are insidious and hard to be detected due to limited biomarkers. …”
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    Influência de um protocolo de criopreservação no rendimento in vitro de células-tronco derivadas do tecido adiposo Effect of a cryopreservation protocol on the in vitro yield of ad... by Fernanda Ginani, Diego Moura Soares, Carlos Augusto Galvão Barboza

    Published 2012-09-01
    “…<br>BACKGROUND: Adipose tissue obtained by liposuction may be an accessible source of stem cells for future clinical application in tissue regeneration. …”
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    Glucocorticoids and antivirals for HBV reactivation in onco-hematologic patients by Michela di Fonzo, Andrea Marengo, Alfredo Marzano, Antonella Ferrari, Bruno Monarca, Gianfranco delle Fave, Massimo Marignani

    Published 2010-02-01
    “…In this later autopsy detected cirrhosis, not evident at presentation. This clinical experience suggests that in patients with &lt;span&gt;onco-hematological&lt;/span&gt; and persistent liver function tests alterations in spite of effective antiviral response, glucocorticoids could control the effects of immune response. …”
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  11. 1671
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    Survey on Backdoor Attacks on Deep Learning: Current Trends, Categorization, Applications, Research Challenges, and Future Prospects by Muhammad Abdullah Hanif, Nandish Chattopadhyay, Bassem Ouni, Muhammad Shafique

    Published 2025-01-01
    “…Such attacks are usually referred to as Trojan or backdoor attacks and are very stealthy and hard to detect. In this paper, we highlight the complete attack surface that can be exploited to inject hidden malicious functionality (backdoors) in machine learning models. …”
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    Non-invasive biopsy diagnosis of diabetic kidney disease via deep learning applied to retinal images: a population-based study by Ziyao Meng, MEng, Zhouyu Guan, MD, Shujie Yu, MBBS, Yilan Wu, BSc, Yaoning Zhao, BSc, Jie Shen, PhD, Cynthia Ciwei Lim, MMed, Tingli Chen, MD, Dawei Yang, PhD, An Ran Ran, PhD, Feng He, MSc, Haslina Hamzah, BSc, Sarkaaj Singh, MSc, Anis Syazwani Abd Raof, MSc, Jian Wen Samuel Lee-Boey, MBBS, ProfMBBS Soo-Kun Lim, MBBS, ProfMD Xufang Sun, MBBS, Shuwang Ge, MD, ProfMD Gang Xu, MD, Prof Hua Su, MD, Yang Cheng, MD, Feng Lu, PhD, ProfPhD Xiaofei Liao, PhD, ProfPhD Hai Jin, PhD, Chenxin Deng, MMed, Lei Ruan, MD, ProfMD Cuntai Zhang, MD, Chan Wu, MD, ProfMD Rongping Dai, MD, Yixiao Jin, MSc, Wenxiao Wang, PhD, Tingyao Li, BSc, Ruhan Liu, PhD, Jiajia Li, PhD, Jia Shu, BEng, Yuwei Lu, MBBS, Xiangning Wang, MD, Qiang Wu, MD, Yiming Qin, BEng, Jin Tang, MD, Xiaohua Sheng, MD, Qiong Jiao, MD, ProfPhD Xiaokang Yang, MD, ProfPhD Minyi Guo, MD, Gareth J McKay, PhD, ProfPhD Ruth E Hogg, PhD, Gerald Liew, MBBS, Evelyn Yi Lyn Chee, PhD, ProfPhD Wynne Hsu, PhD, ProfPhD Mong Li Lee, PhD, Simon Szeto, MBChB, ProfMD Andrea O Y Luk, MBChB, ProfMD Juliana C N Chan, MBChB, Carol Y Cheung, PhD, Gavin Siew Wei Tan, FRCSEd, Yih-Chung Tham, PhD, ProfMD PhD Ching-Yu Cheng, PhD, Charumathi Sabanayagam, MD PhD, ProfPhD Lee-Ling Lim, MD PhD, ProfMD PhD Weiping Jia, MD PhD, ProfMD PhD Huating Li, MD PhD, Bin Sheng, Prof, Tien Yin Wong, Prof

    Published 2025-05-01
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  17. 1677

    EZSCAN for undiagnosed type 2 diabetes mellitus: A systematic review and meta-analysis. by Antonio Bernabe-Ortiz, Andrea Ruiz-Alejos, J Jaime Miranda, Rohini Mathur, Pablo Perel, Liam Smeeth

    Published 2017-01-01
    “…<h4>Objectives</h4>The EZSCAN is a non-invasive device that, by evaluating sweat gland function, may detect subjects with type 2 diabetes mellitus (T2DM). …”
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