[7]
Schmarzo, B. Big data: Understanding how data powers big business; Wiley: Indianapolis, 2013.
[11]
Raghupathi, W.; Raghupathi, V. An overview of health analytics. J. Health Med. Inform., 2013, 4, 132.
[16]
Singh, N.; Singh, S. Object classification to analyze medical imaging data using deep learning; Int Conf Innov Inf Embed Commun Syst, 2018, pp. 1-4.
[22]
Kumari, V.A.; Chitra, R. Classification of diabetes disease using support vector machine. Int. J. Eng. Res. Appl., 2013, 3(2), 1797-1801.
[23]
Ba-alwi, F.M.; Hintaya, H.M. Comparative study for analysis of the prognostic in hepatitis data: Data mining approach. Int. J. Sci. Eng. Res., 2013, 4(8), 680-685.
[24]
Fathima, A.S.; Manimeglai, D. Predictive analysis for the arbovirus-dengue using SVM classification. Int J Eng Technol., 2012, 2(3), 521-527.
[25]
Tarmizi, N.A.; Jamaluddin, F. Malaysia dengue outbreak detection using data mining models. J Next Gener Inf Technol., 2013, 4, 96-107.
[26]
Rajeswari, P.; Reena, G.S. Analysis of liver disorder using data mining algorithm. Glob J Comput Sci Technol., 2012, 10(14), 49.
[27]
Kousarrizi, M.R.N.; Seiti, F.; Teshnehlab, M. An experimental comparative study on thyroid disease diagnosis based on feature subset selection and classification. Int J Electr Comput Sci., 2012, 12(1), 13-19.
[28]
Chaurasia, V.; Pal, S. Data mining approach to detect heart disease. Int J Adv Comput Sci Inf Technol., 2013, 2(4), 56-66.
[30]
Dhanashree, S.; Mayur, P.; Shruti, D. Heart disease prediction system using naive Bayes. Int. J. Enhanc. Res. Sci. Technol. Eng., 2013, 2(3), 290-294.
[31]
Sarwar, A.; Sharma, V. Intelligent naïve Bayes approach to diagnose diabetes type-2. Int J Comput Appl Chall Netw Intell Comput Technol., 2012, 3(14–16)
[32]
Shajahaan, S.S.; Shanthi, S.; Manochitra, V. Application of data mining techniques to model breast cancer data. Int. J. Emerg. Technol. Adv. Eng., 2013, 3(11), 362-369.
[33]
Sivakami, K.; Application, C. Mining big data: Breast cancer prediction using DT-SVM hybrid model. Int J Sci Eng Appl Sci., 2015, 1(5), 418-429.
[35]
Shrivastava, S.S.; Sant, A.; Aharwal, R.P. An overview on data mining approach on breast cancer data. Int J Adv Comput Res., 2013, 3, 256-262.
[42]
Davenport, T.H.; Harris, J.G. Competing on analytics, the new science of winning; Harvard Business School Publishing Corporation: Boston, MA, 2007.
[46]
Gupta, V.; Rathmore, N. Deriving business intelligence from unstructured data. Int J Inf Comput Technol., 2013, 3(9), 971-976.
[48]
Williams, N; Ferdinand, NP; Croft, R Project management maturity in the age of big data. Int. J. Manag. Proj. Bus., 2014, 7(2), 311-317.
[58]
Ratia, M.; Myllärniemi, J. Beyond IC 4.0: The future potential of BI-tool utilization in the private healthcare. Proc IFKAD, 2018, 1-13.
[62]
Groves, P; Kayyali, B; Knott, D; Van Kuiken, S. The ‘big data’ revolution in healthcare: Accelerating value and innovation. McKinsey Company, 2015.
[70]
Ismail, A.; Shehab, A.; El-Henawy, I.M. Security in smart cities: Models, applications, and challenges. In: In: Healthcare analysis in smart big data analytics: Reviews, challenges and recommendations; Springer: Cham, Switzerland, 2019; pp. 27-45.
[76]
Islam, M.S.; Hasan, M.M.; Wang, X.; Germack, H. A systematic review on healthcare analytics: Application and theoretical perspective of data mining. Healthcare; Multidisciplinary Digital Publishing Institute: Basel, Switzerland, 2018, p. 54.
[81]
Marconi, K.; Dobra, M.; Thompson, C. The use of big data in healthcare. In: Big data and business analytics; Liebowitz, J., Ed.; CRC Press: Boca Raton, 2012; pp. 229-248.
[82]
Manyika, J.; Chui, M.; Brown, B.; Bughin, J.; Dobbs, R.; Roxburgh, C. Big data: The next frontier for innovation, competition, and productivity; McKinsey Global Institute: Washington, 2011.
[83]
Madsen, L.B. Data-driven healthcare: How analytics and BI are transforming the industry; Wiley: Hoboken, 2014.
[84]
Raguseo, E. Big data technologies: An empirical investigation on their adoption, benefits and risks for companies. Int. J. Inf. Manage, 2018, 38(1), 187-195.
[85]
Bartuś, K.; Batko, K.; Lorek, P. Diagnosis of the use of big data in organizations – selected research results Economic Informatics, 2017, 3(45), 9-20.
[86]
Boerma, T.; Requejo, J.; Victora, C.G.; Amouzou, A.; George, A.; Agyepong, I.; Barroso, C.; Barros, A.J.D.; Bhutta, Z.A.; Black, R.E.; Borghi, J.; Buse, K.; Aguirre, L.C.; Chopra, M.; Chou, D.; Chu, Y.; Claeson, M.; Daelmans, B.; Davis, A.; DeJong, J.; Diaz, T.; El Arifeen, S.; Ewerling, F.; Fox, M.; Gillespie, S.; Grove, J.; Guenther, T.; Haakenstad, A.; Hosseinpoor, A.R.; Hounton, S.; Huicho, L.; Jacobs, T.; Jiwani, S.; Keita, Y.; Khosla, R.; Kruk, M.E.; Kuo, T.; Kyobutungi, C.; Langer, A.; Lawn, J.E.; Leslie, H.; Liang, M.; Maliqi, B.; Manu, A.; Masanja, H.; Marchant, T.; Menon, P.; Moran, A.C.; Mujica, O.J.; Nambiar, D.; Ohiri, K.; Park, L.A.; Patton, G.C.; Peterson, S.; Piwoz, E.; Rasanathan, K.; Raj, A.; Ronsmans, C.; Saad-Haddad, G.; Sabin, M.L.; Sanders, D.; Sawyer, S.M.; da Silva, I.C.M.; Singh, N.S.; Somers, K.; Spiegel, P.; Tappis, H.; Temmerman, M.; Vaz, L.M.E.; Ved, R.R.; Vidaletti, L.P.; Waiswa, P.; Wehrmeister, F.C.; Weiss, W.; You, D.; Zaidi, S. Countdown to 2030: Tracking progress towards universal coverage for reproductive, maternal, newborn, and child health.
Lancet, 2018,
391(10129), 1538-1548.
[
http://dx.doi.org/10.1016/S0140-6736(18)30104-1] [PMID:
29395268]
[96]
Vijayarani, S. Liver disease prediction using SVM and naïve Bayes algorithms. Int J Sci Eng Technol Res., 2015, 4(4), 816-820.
[97]
Applying big data analytics in bioinformatics and medicine; Lytras, M.D.; Papadopoulou, P., Eds.; IGI Global: Hershey, 2017.
[104]
Schulte, T; Bohnet-Joschko, S How can big data analytics support people-centred and integrated health services: A scoping review Int. J. Integ. Care, 2022 Jun 16;22(2), 23.
[106]
Batko, K Possibilities of using big data in healthcare Annals of the College of Economic Analysis, 2016, 42, 267-282.
[107]
Bi, Z.; Cochran, D. Big data analytics with applications. J Manag Anal., 2014, 1(4), 249-265.
[108]
Bollier, D.; Firestone, C.M. The promise and peril of big data; Aspen Institute, Communications and Society Program: Washington, D.C., 2010.
[109]
Carter, P. Big data analytics: Future architectures, skills and roadmaps for the CIO. In: White paper; IDC, sponsored by SAS, 2011.
[111]
Fredriksson, C. Organizational knowledge creation with big data: A case study of the concept and practical use of big data in a local government context. 2016.