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Sepsis Detection in newborn infants - Diagnosis using fuzzy inference system- A Review

M.S. Kalas1 , Nikita D. Deshpande2

Section:Review Paper, Product Type: Journal Paper
Volume-9 , Issue-5 , Page no. 43-46, May-2021

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v9i5.4346

Online published on May 31, 2021

Copyright © M.S. Kalas, Nikita D. Deshpande . 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.

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IEEE Style Citation: M.S. Kalas, Nikita D. Deshpande, “Sepsis Detection in newborn infants - Diagnosis using fuzzy inference system- A Review,” International Journal of Computer Sciences and Engineering, Vol.9, Issue.5, pp.43-46, 2021.

MLA Style Citation: M.S. Kalas, Nikita D. Deshpande "Sepsis Detection in newborn infants - Diagnosis using fuzzy inference system- A Review." International Journal of Computer Sciences and Engineering 9.5 (2021): 43-46.

APA Style Citation: M.S. Kalas, Nikita D. Deshpande, (2021). Sepsis Detection in newborn infants - Diagnosis using fuzzy inference system- A Review. International Journal of Computer Sciences and Engineering, 9(5), 43-46.

BibTex Style Citation:
@article{Kalas_2021,
author = {M.S. Kalas, Nikita D. Deshpande},
title = {Sepsis Detection in newborn infants - Diagnosis using fuzzy inference system- A Review},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2021},
volume = {9},
Issue = {5},
month = {5},
year = {2021},
issn = {2347-2693},
pages = {43-46},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5335},
doi = {https://doi.org/10.26438/ijcse/v9i5.4346}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v9i5.4346}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5335
TI - Sepsis Detection in newborn infants - Diagnosis using fuzzy inference system- A Review
T2 - International Journal of Computer Sciences and Engineering
AU - M.S. Kalas, Nikita D. Deshpande
PY - 2021
DA - 2021/05/31
PB - IJCSE, Indore, INDIA
SP - 43-46
IS - 5
VL - 9
SN - 2347-2693
ER -

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Abstract

The detection of a health problem, illness, disability, or other condition that an individual may have is known as disease diagnosis. Large data sets are available; however, the tools that can accurately evaluate trends and make predictions are limited. Traditional methods of diagnosing diseases are considered to be not effective in getting accuracy and prone to error. Artificial Intelligence (AI) is being used to forecast the future. AI with predictive techniques enables to provide auto diagnosis and reduces detection errors compared to exclusive human expertise. In this paper we have taken review of sepsis detection in newborn infants using techniques of AI, like Fuzzy Logic and identified limitations of these studies. The aim of this research paper is to reveal some key insights into medical techniques. Based on a series of open problems and challenges, the paper also suggests some directions for potential research on AI-based diagnostics systems.

Key-Words / Index Term

Disease, diagnosis, Sepsis Detection, Fuzzy logic

References

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