Deduction of Efficient Scanning Machines using Big Data Technology
Caroline El Fiorenza J1, Abishek R2, Shikhar Saxena3, Vaibhav Mukundan4
1Caroline El Fiorenza J, Assistant Professor, Research Scholar, Department of Computer Science Engineering, UG, SRM Institute of Science and Technology, Chennai, India.
2Abishek R , Research Scholar, Department of Computer Science Engineering, UG, SRM Institute of Science and Technology, Chennai, India.
3Shikhar Saxena, Research Scholar, Department of Computer Science Engineering, UG, SRM Institute of Science and Technology, Chennai, India.
4Vaibhav Mukundan, Research Scholar, Department of Computer Science Engineering, UG, SRM Institute of Science and Technology, Chennai, India.
Manuscript received on November 10, 2019. | Revised Manuscript received on November 17, 2019. | Manuscript published on 30 November, 2019. | PP: 3770-3776 | Volume-8 Issue-4, November 2019. | Retrieval Number: D8143118419/2019©BEIESP | DOI: 10.35940/ijrte.D8143.118419
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Nowadays, the advancement in the field of information technology has witnessed stupendous growth in various industries, especially the medical imaging technologies in the healthcare industry. However, these advancements in the different technologies have not only made the data bigger but also a bit difficult to process and handle it. Though, these advancements may have resulted in huge amount of unnecessary data, it still cannot be considered as a major problem in today’s world as nowadays, the various advancements in technologies such as Big Data Analytics, Cloud Computing and several others, have made it really easy and effortless for storing huge amount of datasets and handling them. One of the boon that the advancement in technology has given to the world in the field of healthcare industry is the evolution of the scanning machines which can be used for the diagnosis of different diseases and to assemble the conclusions in the form of various medical reports for different scans such as ECG (Electrocardiogram), MRI(Magnetic Resonance Imaging) Brain scans, Ultrasounds, X-Rays, CT-Scanners and much more. But, the interesting part here is that though these scanning machines have their own advantages, one of the main disadvantages of them is that the efficiency of the results produced by them are yet to be known when comparing their performance’s to justify their enormous costs. Therefore, in the paper, the key challenges and various methodologies are being investigated in the healthcare industry with prime focus on comparing the scanning machines such as ECG, MRI, and Ultrasoundetc. by using Big Data Analytics. The various manufacturers of the scanning devices which are used by the hospitals or diagnostic centers have already fixed their price to such a high level that, even the hospitals have to spend lots of money to buy those machines and install them. Therefore, as a management side it becomes difficult to cope up with the performance related cost effectiveness of machines, which even shatters the trust of patients related to technical issues with a particular hospital. The prime aim is to focus on the precise implementation, performance efficiency and cost effectiveness of all the medical scans. The idea can also be implemented in improving theperformance along with the cost effectiveness of machines and devices other than the medical industry as well.
Keywords: Big Data Analytics, Health Analytics, Medical Imaging, SQL database, Text Analytics, Feature Extraction using Python.
Scope of the Article: Health Monitoring and Life Prediction of Structures.