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  • Open Access

    ARTICLE

    Comparison of Treatment Response and Survival Profiles Between Drug-Eluting Bead Transarterial Chemoembolization and Conventional Transarterial Chemoembolization in Chinese Hepatocellular Carcinoma Patients: A Prospective Cohort Study

    Ping Wen*, Sheng-Duo Chen*, Jia-Rui Wang, Ying-He Zeng*

    Oncology Research, Vol.27, No.5, pp. 583-592, 2019, DOI:10.3727/096504018X15368325811545

    Abstract This study evaluated the difference in treatment response and survival profiles between drug-eluting bead transarterial chemoembolization (DEB-TACE) and conventional transarterial chemoembolization (cTACE) treatments in Chinese hepatocellular carcinoma (HCC) patients. A total of 120 HCC patients were consecutively enrolled in this prospective cohort study, which showed that DEB-TACE achieved higher complete response (CR) (30.8%) compared with cTACE (7.4%) with no difference in overall response rate (ORR) for patients treated with DEB-TACE and cTACE (80.8% vs. 73.5%). In addition, DEB-TACE was associated with a lower rate of progressive disease (PD) compared with cTACE (1.9% vs. 11.8%). With respect to survival, patients in… More >

  • Open Access

    ARTICLE

    Dynamic Ensemble Multivariate Time Series Forecasting Model for PM2.5

    Narendran Sobanapuram Muruganandam, Umamakeswari Arumugam*

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 979-989, 2023, DOI:10.32604/csse.2023.024943

    Abstract In forecasting real time environmental factors, large data is needed to analyse the pattern behind the data values. Air pollution is a major threat towards developing countries and it is proliferating every year. Many methods in time series prediction and deep learning models to estimate the severity of air pollution. Each independent variable contributing towards pollution is necessary to analyse the trend behind the air pollution in that particular locality. This approach selects multivariate time series and coalesce a real time updatable autoregressive model to forecast Particulate matter (PM) PM2.5. To perform experimental analysis the data from the Central Pollution… More >

  • Open Access

    ARTICLE

    Statistical models for evaluating the genotype-environment interaction in maize (Zea mays L.)

    Kandus1 M, D Almorza3, R Boggio Ronceros2, JC Salerno1

    Phyton-International Journal of Experimental Botany, Vol.79, pp. 39-46, 2010, DOI:10.32604/phyton.2010.79.039

    Abstract Our objective was to determine the genotype-environment interaction (GxE) in a hybrid integrated by maize lines either carrying or not balanced lethal systems. Experiments were conducted in three locations over a period of two years considering each yearlocation combination as a different environment. Yield data were analysed using the Additive Main Effects and Multiplicative Interaction (AMMI) model and the Sites Regression Analysis (SREG). Results were represented by biplots. The AMMI analysis was the best model for determining the interaction. More >

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