More Accurate Organ Recipient Identification Using Survey Informatics of New Age Technologies
- 10.2991/ahis.k.210913.002How to use a DOI?
- HLA matching algorithm, Internet of Things, Organ Procurement, Organ Transplantation, Traffic Control
Organ transplantation is a miraculous achievement for most of the end-stage diseases caused due to organ failure. Providing the organ to the most accurate recipient is always a challenge. The survival prediction of the recipient based on various health and environmental/infrastructural data (e.g.: live traffic) is not considered in the current selection algorithms, thus reducing the healthy lifespan of the recipient. The objective of this research is to do an in-depth analysis of the historical transplantation data for the organ (kidney) and figure out statistical evidence of various parameters which are affecting the survival time of the organ recipient. Both univariant and covariant analysis (impact in conjunction with other varying parameters) of these data parameters are studied. The result of this study was further analyzed to identify such parameters which vary frequently with time but also impact the predicted survival curve of the recipient. The research focuses on the benefit of new-age technology such as IoT in accurately predicting the most suitable recipient with a longer survival curve. The research ultimately wants to bring out an efficient recipient identification mechanism for organ procurement and transplantation
- © 2021, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Benita Jose Chalissery AU - V. Asha AU - B. Meenakshi Sundaram PY - 2021 DA - 2021/09/13 TI - More Accurate Organ Recipient Identification Using Survey Informatics of New Age Technologies BT - Proceedings of the 3rd International Conference on Integrated Intelligent Computing Communication & Security (ICIIC 2021) PB - Atlantis Press SP - 6 EP - 13 SN - 2589-4900 UR - https://doi.org/10.2991/ahis.k.210913.002 DO - 10.2991/ahis.k.210913.002 ID - Chalissery2021 ER -