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    Comparative evaluation of feature reduction methods for drug response prediction by Farzaneh Firoozbakht, Behnam Yousefi, Olga Tsoy, Jan Baumbach, Benno Schwikowski

    Published 2024-12-01
    “…Our analysis employs six distinct machine learning models, with a total of more than 6,000 runs to ensure a robust evaluation. Our findings indicate that transcription factor activities outperform other methods in predicting drug responses, effectively distinguishing between sensitive and resistant tumors for seven of the 20 drugs evaluated.…”
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    Article
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    Comparative evaluation of lethal outcome prediction methods in severely burned patients by O. O. Zavorotniy, E. V. Zinoviev, V. G. Volkov, D. V. Kostyakov, D. H. Halipaeva, A. V. Semiglazov, T. Z. Gogohiya

    Published 2022-03-01
    “…Despite the ease of use and the maximum prevalence of existing models, the assessment of the outcome in each of them is questionable, since the emphasis in different indices is on different indicators, avoiding the overall clinical picture of the disease.Objective: Comparative analysis of the effectiveness of methods for predicting a lethal outcome in patients with extensive skin burns.Material and мethods: Calculated characteristics of known in the literature and widely used Baux rules, Frank index, probit analysis and a new method of logistic regression were obtained and applied to evaluate the results of treatment of 282 adult patients with extensive skin burns, hospitalized in the Department of Anesthesiology and Intensive Care of the Thermal Injuries Unit, Saint-Petersburg I. …”
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    Evaluation of Data Mining and Artificial Intelligence Methods to Predict Daily Precipitation by Yaseen Ahmed Hamaamin

    Published 2025-05-01
    “…The results of the ANN and ANFIS testing methods were 0.55 and 0.62, respectively. Outcomes of the study showed that the ANN model may have overfitted the results in the calibration section of the process compared to the ANFIS method, which performed better in the testing section of the evaluation process. …”
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    Software refactoring prediction evaluation method based on deep learning models by Yichi ZHANG, Yang ZHANG, Yanlei LI, Kun ZHENG, Wei LIU

    Published 2024-12-01
    “…Aiming at the lack of research on the performance of deep learning models in predicting software refactoring in the current field, a deep learning-based software refactoring prediction evaluation method was proposed to assess the refactoring predictive performance of these models. …”
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    Evaluation of the PANS method for the prediction of the fluid flow in a cyclone separator by Bitar, Zaher, Uystepruyst, David, Beaubert, François, Méresse, Damien, Morin, Céline

    Published 2023-05-01
    “…In this work, Partially Averaged Navier–Stokes (PANS) method is proposed to simulate the fluid flow inside a gas cyclone. …”
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    Performance evaluation of extreme value prediction methods for bridge traffic load effects by Miaomiao Xu, Xiao-Yi Zhou, Jie Shen, Deliang Ding, Sugong Cao, C. S. Cai

    Published 2025-08-01
    “…The analysis is then extended to more realistic scenarios, where long-run simulations provide benchmark results for evaluating the accuracy of each method. Based on the findings, recommendations are provided for selecting the most suitable prediction method, considering factors such as sample size, time interval, and the type of load effect. …”
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    Evaluating statistical methods to predict indoor black carbon in an urban birth cohort by Sherry WeMott, Grace Kuiper, Sheena E. Martenies, Matthew D. Koslovsky, William B. Allshouse, John L. Adgate, Anne P. Starling, Dana Dabelea, Sheryl Magzamen

    Published 2025-06-01
    “…However, people spend 90 % of their time indoors, with 70 % of that time spent at home, which may result in misclassification of air pollution exposure when using data reflecting ambient concentrations. In this study, we evaluated methods to predict residential indoor black carbon (BC) from outdoor BC, PM2.5, and housing characteristics to support future efforts in estimating personal air pollution exposure. …”
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    Prediction and evaluation method for development effect of shale oil storage volume fracturing by XU Ning, CHEN Zhewei, XU Wanchen, WANG Ling, CUI Xiaolei, JIANG Meizhong, ZHAN Changwu

    Published 2024-10-01
    “…By controlling the average rate of discharge and production within the range of 6~8 m3/(d·km), which aligns with the rates of oil drainage and imbibition, higher oil recovery and a lower liquid-to-oil ratio are achieved. This prediction method for maximum recoverable oil post-single well fracturing provides a basis for the economic benefit evaluation, production system optimization, and fracturing cost control of energy storage fracturing. …”
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    Understanding the impact of covariates for trachoma prevalence prediction using geostatistical methods by Misaki Sasanami, Ibrahim Almou, Adam Nouhou Diori, Ana Bakhtiari, Nassirou Beidou, Donal Bisanzio, Sarah Boyd, Clara R. Burgert-Brucker, Abdou Amza, Katherine Gass, Boubacar Kadri, Fikreab Kebede, Michael P. Masika, Nicholas P. Olobio, Fikre Seife, Abdoul Salam Youssoufou Souley, Amsayaw Tefera, Amir B. Kello, Anthony W. Solomon, Emma M. Harding-Esch, Emanuele Giorgi

    Published 2025-06-01
    “…To this end, we assessed the ability of spatial covariates to explain the spatial variation of TF prevalence and to reduce uncertainty in the assessment of TF elimination for pre-defined evaluation units (EUs). Methods We used data from Tropical Data-supported population-based trachoma prevalence surveys conducted in EUs in Ethiopia, Malawi, Niger, and Nigeria between 2016 and 2023. …”
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    Evaluation of machine learning methods for prediction of heart failure mortality and readmission: meta-analysis by Hamed Hajishah, Danial Kazemi, Ehsan Safaee, Mohammad Javad Amini, Maral Peisepar, Mohammad Mahdi Tanhapour, Arian Tavasol

    Published 2025-04-01
    “…The neural network model achieved the highest overall AUC for mortality prediction (0.808), while the support vector machine performed best for readmission prediction (AUC 0.733). …”
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