Article


Big Data and Neural Network in Cardiology Health Prediction

Agustín Joison, N.1*, Raul Barcudi, J.2, Enrique Majul, A.3, Sergio Ruffino, A.4, Juan DE Mateo Rey, J.5, Agustin Joison, M.6 & Gustavo Baiardi7

1Chairman of Biological Department, Faculty of Chemical Sciences, Catholic University of Córdoba, Avenida Armada Argentina
2Professor and Chairman of Coronary Unit, University Reina Fabiola Clinic, Córdoba, Argentina
3Chairman of Química III, Dean of Faculty of Health Sciences, Catholic University of Córdoba, Córdoba, Argentina
4Professor Assistant of Química III, Faculty of Health Sciences, Catholic University of Córdoba, Córdoba, Argentina
5Professor of Química III, Faculty of Health Sciences, Catholic University of Córdoba, Córdoba, Argentina
6Systems Engineer, Globant Business, Avenida Colón 610, Córdoba, Argentina
7Assistant professor, Institute of Biological and Technological Research (IIBYT-CONICET), National University of Córdoba, Faculty of Chemical Sciences, Catholic University of Córdoba, Avenida Armada Argentina 3555, Córdoba, Argentina

Dr. Agustín Joison, N., Chairman of Biological Department, Faculty of Chemical Sciences, Catholic University of Córdoba, Avenida Armada Argentina.

Keywords: Big Data; Cardiology; Algorithms; Neural Network; Health

Abstract

In health as in other areas there is availability of information, which can be collected in digital and continuous format; this phenomenon that is currently called Big Data that includes four research themes in the current literature, namely: 1.information, 2. technology, 3. methods, 4. Impact. The term Big Data from 1990 began to be used as a synonym for the collection, automation and recording of large amounts of data, which introduced an innovation in the treatment of information improving decision-making in many areas of our society. In the area of cardiology health research, clinical diagnosis, prognosis and therapy of patients, accurate and orderly data are fundamental tools in the access and analysis of the right information. The current era of computer, systems and software enabled a better interpretation of Big Data, and improved deep learning and a successful advancement in machine learning algorithms. Big Data is now transformed into a tool that enables for healthcare stakeholders to implement three types of analysis techniques; 1: historical (descriptive study), 2: future results (predictive study), 3: current situation (prescriptive study). This technology, which was born with some uncertainty and Luke warmness of professionals to accept this revolution regarding the information it provides, ends as a new paradigm in health care by understanding of algorithms and machine learning importance.

View Full Text | Download PDF

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Total Articles Published

7
2
4


Track Your Article







Highlights


Cient Periodique is a ‘Gold’ open access publisher that aspires to offer absolute free, unrestricted access to the valuable research information

We welcome all the eminent authors to submit your valuable paper

Cient Periodique invites the participation of honourable Editors and Authors

CPQ Journals provide Certificates for publication

Cient Periodique also offers memberships for potential Authors

Best Articles will be appreciated with the provision of corresponding Certificate