Journal of Biomedical and Sustainable Healthcare Applications


Contributions on Computational Intelligence in the Medical Sector



Journal of Biomedical and Sustainable Healthcare Applications

Received On : 15 August 2020

Revised On : 18 September 2020

Accepted On : 22 October 2020

Published On : 05 January 2021

Volume 01, Issue 01

Pages : 001-008


Abstract


Patients' treatments are becoming more personalized as healthcare becomes more commodified. Meeting this need requires not just a large allocation of capital, but also a comprehensive application of information, resulting in efforts like electronic health record standards. The quantity of medical data accessible for analytics and data extraction will grow rapidly as these become more mainstream. This is accompanied by an increase in new methods for non-invasive assessment and collection of medically important data in different forms, such as signals and pictures. Despite problems with standardization and availability, the enormous quantity of data that results is a significant tool for the machine learning industry. Biomedical CI technologies are already flourishing because of getting into this data stream. The legislative session "Computer science and information Intelligence in Biology and medicine" at ESANN addresses some of the field's most pressing issues. This paper introduces the session by highlighting a few of the submissions and pointing out possibilities and difficulties for CI in biomedicine.


Keywords


Computational Intelligence (CI), Machine Learning (ML), Big Data (BD).


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Author(s) thanks to Stevens Institute of Technology for research lab and equipment support.


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Cite this article


Helen Tucci Wang, “Contributions on Computational Intelligence in the Medical Sector”, Journal of Biomedical and Sustainable Healthcare Applications, vol.1, no.1, pp. 001-008, January 2021. doi: 10.53759/0088/JBSHA202101001.


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© 2021 Helen Tucci Wang. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.