Survey on Perception of People Regarding Utilization of Computer Science & Information Technology in Manipulation of Big Data, Disease Detection & Drug Discovery
Subject Areas : Data MiningMd Sarowar 1 , Azim Khan 2 , Maruf Shakil 3 , Mohammad Ullah 4
1 - Computer science & engineering, east west university, bangladesh
2 - Computer science and engineering, east west university, bangladesh.
3 - Dept of computer science and engineering, east west university, bangladesh.
4 - dept of computer science and engineering, east west university, bangladesh.
Keywords: disease detection, Big Data, computer aided automated system, drug discovery,
Abstract :
this research explores the manipulation of biomedical big data and diseases detection using automated computing mechanisms. As efficient and cost effective way to discover disease and drug is important for a society so computer aided automated system is a must. This paper aims to understand the importance of computer aided automated system among the people. The analysis result from collected data contributes to finding an effective result that people have enough understanding and much better knowledge about big data and computer aided automated system. moreover, perspective and trustworthiness of people regarding recent advancement of computer aided technologies in biomedical science have been demonstrated in this research. however, appearance of big data in the field of medical science and manipulation of those data have been concentrated on this research. Finally suggestions have been developed for further research related to computer technology in manipulation of big data, disease detection and drug discovery.
[1] Michael Riegler, Konstantin Pogorelov, Jonas Markussen, Mathias Lux, Håkon Kvale Stensland, Thomas de Lange, Carsten Griwodz, Pål Halvorsen, Dag Johansen, Peter T. Schmidt, and Sigrun L. Eskeland. 2016. Computer aided disease detection system for gastrointestinal examinations. In Proceedings of the 7th International Conference on Multimedia Systems (MMSys '16). ACM, New York, NY, USA, Article 29, 4 pages. DOI: https://doi.org/10.1145/2910017.2910629
[2] John Rooksby, Parvin Asadzadeh, Alistair Morrison, Claire McCallum, Cindy Gray, and Matthew Chalmers. 2016. Implementing ethics for a mobile app deployment. In Proceedings of the 28th Australian Conference on Computer-Human Interaction (OzCHI '16). ACM, New York, NY, USA, 406-415. DOI: https://doi.org/10.1145/3010915.3010919
[3] S. E. Polykalas, G. N. Prezerakos, F. D. Chrysidou and E. D. Pylarinou, "Mobile apps and data privacy: When the service is free, the product is your data," 2017 8th International Conference on Information, Intelligence, Systems & Applications (IISA), Larnaca, 2017, pp. 1-5.
[4] SU MON KYWE; Yingjiu LI; HONG, Jason; and CHENG, Yao. Dissecting developer policy violating apps: Characterization and detection. (2016). Proceedings of the 11th IEEE International Conference on Malicious and Unwanted Software (Malcon): October 18-21, Fajardo, Puerto Rico. Research Collection School Of Information Systems.
[5] S. Karthick and S. Binu, "Android security issues and solutions," 2017 International Conference on Innovative Mechanisms for Industry Applications (ICIMIA), Bangalore, 2017, pp. 686-689.
[6] "Grounded Theory", The Good Research Guide by Denscombe. Chapter 14 page no. 283.
[7] V. S. Pendyala and S. Figueira, "Automated Medical Diagnosis from Clinical Data," 2017 IEEE Third International Conference on Big Data Computing Service and Applications (BigDataService), San Francisco, CA, 2017, pp. 185-190.doi: 10.1109/BigDataService.2017.14
[8] Fabricio F. Costa, Big data in biomedicine, Drug Discovery Today, Volume 19, Issue 4, 2014, Pages 433-440, ISSN 1359-6446, https://doi.org/10.1016/j.drudis.2013.10.012.
[9] Aurelle Tchagna Kouanou, Daniel Tchiotsop, Romanic Kengne, Djoufack Tansaa Zephirin, Ngo Mouelas Adele Armele, René Tchinda, An optimal big data workflow for biomedical image analysis,Informatics in Medicine Unlocked,Volume 11,2018,Pages 68-74,ISSN 2352-9148, https://doi.org/10.1016/j.imu.2018.05.001.
[10] M. D. Naeemi, J. Ren, N. Hollcroft, A. M. Alessio and S. Roychowdhury, "Application of big data analytics for automated estimation of CT image quality," 2016 IEEE International Conference on Big Data (Big Data), Washington, DC, 2016, pp. 3422-3431.doi: 10.1109/BigData.2016.7841003.
[11] Masouleh, M. F., Kazemi, M. A. A., Alborzi, M., & Eshlaghy, A. T. (2017). Identification of electrocardiogram signals using internet of things based on combinatory classification. International Journal of Modeling, Simulation, and Scientific Computing, 8(03), 1750035.
[12] Sarowar MDG (2018) Emergence of Automated Computing Technologies in Biomedical Disease and Drug Discovery. J Biomed Syst Emerg Technol 5: 117.
[13] Rahman A., Nimmy S.F., Sarowar G. (2019) Developing an Automated Machine Learning Approach to Test Discontinuity in DNA for Detecting Tuberculosis. In: Xu J., Cooke F., Gen M., Ahmed S. (eds) Proceedings of the Twelfth International Conference on Management Science and Engineering Management. ICMSEM 2018. Lecture Notes on Multidisciplinary Industrial Engineering. Springer, Cham
[14] Sarowar, M. G., Kamal, M. S., & Dey, N. (2019). Internet of Things and Its Impacts in Computing Intelligence: A Comprehensive Review – IoT Application for Big Data. In N. Dey, & S. Tamane (Eds.), Big Data Analytics for Smart and Connected Cities (pp. 103-136). Hershey, PA: IGI Global. doi:10.4018/978-1-5225-6207-8.ch005
[15] Hassanien, A. E. (Ed.), Dey, N. (Ed.), Borra, S. (Ed.). (2019). Medical Big Data and Internet of Medical Things. Boca Raton: CRC Press.