___

• [1] Nazari, Elham, Mohammad Hasan Shahriari, and Hamed Tabesh. "BigData analysis in healthcare: apache hadoop, apache spark and apache flink." Frontiers in Health Informatics 8.1 (2019): 14.
• [2] Palanisamy, Venketesh, and Ramkumar Thirunavukarasu. "Implications of big data analytics in developing healthcare frameworks–A review." Journal of King Saud University-Computer and Information Sciences 31.4 (2019): 415-425.
• [3] Kumar, Sunil, and Maninder Singh. "Big data analytics for healthcare industry: impact, applications, and tools." Big data mining and analytics 2.1 (2018): 48-57.
• [4] Bahri, Safa, et al. "Big data for healthcare: a survey." IEEE access 7 (2018): 7397-7408.
• [5] Bennett, Derrick A. "How can I deal with missing data in my study?." Australian and New Zealand journal of public health 25.5 (2001): 464-469.
• [6] Graham, John W. "Missing data: Analysis and design". Springer Science & Business Media, (2012).
• [7] Mack, Christina, Zhaohui Su, and Daniel Westreich. "Managing missing data in patient registries: addendum to registries for evaluating patient outcomes: a user’s guide." (2018).
• [8] Rubin, Donald B. "Inference and missing data." Biometrika 63.3 (1976): 581-592.
• [9] Little, Roderick JA, and Donald B. Rubin. Statistical analysis with missing data. Vol. 793. John Wiley & Sons, 2019.
• [10] Ludbrook, John. "Outlying observations and missing values: how should they be handled?." Clinical and experimental pharmacology & physiology 35.5-6 (2008): 670-678.
• [11] Zhang, Zhongheng. "Missing values in big data research: some basic skills." Annals of translational medicine 3.21 (2015).
• [12] Langkamp, Diane L., Amy Lehman, and Stanley Lemeshow. "Techniques for handling missing data in secondary analyses of large surveys." Academic pediatrics 10.3 (2010): 205-210.
• [13] Donders, A. Rogier T., et al. "A gentle introduction to imputation of missing values." Journal of clinical epidemiology 59.10 (2006): 1087-1091.
• [14] Jerez, José M., et al. "Missing data imputation using statistical and machine learning methods in a real breast cancer problem." Artificial intelligence in medicine 50.2 (2010): 105-115.
• [15] Hruschka, Eduardo R., Estevam R. Hruschka, and Nelson FF Ebecken. "Towards efficient imputation by nearest-neighbors: A clustering-based approach." Australasian Joint Conference on Artificial Intelligence. Springer, Berlin, Heidelberg, 2004.
• [16] Zhang, Shichao. "Nearest neighbor selection for iteratively kNN imputation." Journal of Systems and Software 85.11 (2012): 2541-2552.
• [17] Pujianto, Utomo, Aji Prasetya Wibawa, and Muhammad Iqbal Akbar. "K-nearest neighbor (k-NN) based missing data imputation." 2019 5th International Conference on Science in Information Technology (ICSITech). IEEE, 2019.
• [18] Silva-Ramírez, Esther-Lydia, Rafael Pino-Mejías, and Manuel López-Coello. "Single imputation with multilayer perceptron and multiple imputation combining multilayer perceptron and k-nearest neighbours for monotone patterns." Applied Soft Computing 29 (2015): 65-74.
• [19] Purwar, Archana, and Sandeep Kumar Singh. "Hybrid prediction model with missing value imputation for medical data." Expert Systems with Applications 42.13 (2015): 5621-5631.
• [20] Twala, Bhekisipho. "An empirical comparison of techniques for handling incomplete data using decision trees." Applied Artificial Intelligence 23.5 (2009): 373-405.
• [21] Gimpy, Dr, and Minakshi Rajan Vohra. "Estimation of missing values using decision tree approach." Int J Comput Sci Inf Technol 5.4 (2014): 5216-5220.
• [22] Zhang, Shichao, et al. "Missing value imputation based on data clustering." Transactions on computational science I. Springer, Berlin, Heidelberg, 2008. 128-138.
• [23] Zhang, Zhaoyang, Hua Fang, and Honggang Wang. "Multiple imputation based clustering validation (miv) for big longitudinal trial data with missing values in ehealth." Journal of medical systems 40.6 (2016): 1-9.
• [24] Emmanuel, Tlamelo, et al. "A survey on missing data in machine learning." Journal of Big Data 8.1 (2021): 1-37.
• [25] Enders CK. Applied missing data analysis. New York: The Guilford Press; 2010.
• [26] Carpenter, James R., Michael G. Kenward, and Stijn Vansteelandt. "A comparison of multiple imputation and doubly robust estimation for analyses with missing data." Journal of the Royal Statistical Society: Series A (Statistics in Society) 169.3 (2006): 571-584.
• [27] Beale, Evelyn ML, and Roderick JA Little. "Missing values in multivariate analysis." Journal of the Royal Statistical Society: Series B (Methodological) 37.1 (1975): 129-145.
• [28] Carpenter, James R., and Michael G. Kenward. "Missing data in randomised controlled trials: a practical guide." (2007): 199.
• [29] Kanungo, T., Mount, D. M., Netanyahu, N. S., Piatko, C. D., Silverman, R., & Wu, A. Y. "An efficient k-means clustering algorithm: Analysis and implementation." IEEE transactions on pattern analysis and machine intelligence 24.7 (2002): 881-892.
• [30] Cover, Thomas, and Peter Hart. "Nearest neighbor pattern classification." IEEE transactions on information theory 13.1 (1967): 21-27.
• [31] Gou, Jianping, et al. "A generalized mean distance-based k-nearest neighbor classifier." Expert Systems with Applications 115 (2019): 356-372. [32] Allen, David M. "Mean square error of prediction as a criterion for selecting variables." Technometrics 13.3 (1971): 469-475.