Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Subhashini Narayan"'
Autor:
M Fathima Begum, Subhashini Narayan
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 35, Iss 4, Pp 172-182 (2023)
Acute kidney disease is a serious complication characterized by poor short- and long-term outcomes in the intensive care unit. Impairment in renal function of the kidney significantly increases the mortality rate. Early detection of acute kidney dise
Externí odkaz:
https://doaj.org/article/8d4df4e58d424428855854d1e0c27adb
Autor:
Nandakumar P, Subhashini Narayan
Publikováno v:
Intelligent Systems with Applications, Vol 16, Iss , Pp 200131- (2022)
Cardiac disease is the most infected disease in the world nowadays for all ages of people. An emergency need arises to predict cardiac disease accurately in a short time. In this article, hamming distance feature selection method is proposed for the
Externí odkaz:
https://doaj.org/article/fe2e8e5ba82647eb9735de9133e7602a
Publikováno v:
International Journal of Grid and High Performance Computing. 14:1-14
Nowadays, medical diseases are one of the primary causes of death, and it is one the major concerns of developed countries. So, the disease identification process needs a lot of attention since if the diseases are idenfied at the early stage, the rat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::84f6efd2f5f456b95b09f3adf9b90011
https://doi.org/10.4018/ijghpc.316157
https://doi.org/10.4018/ijghpc.316157
Autor:
Nandakumar P, Subhashini Narayan
Publikováno v:
The Open Biomedical Engineering Journal. 16
Deep learning is a sub-field of machine learning that emerged as a noticeable model in the world, specifically for the disease classification field. This work aims to review the state-of-the-art deep learning models in Cardiac Disease prediction by e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c09a522275274474674cb7f87edfa5d5
https://doi.org/10.2174/18741207-v16-e221227-2022-ht27-3589-14
https://doi.org/10.2174/18741207-v16-e221227-2022-ht27-3589-14
Publikováno v:
Lecture Notes in Networks and Systems ISBN: 9789811950896
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::66cd23f1519e54d6889706cf309af5e8
https://doi.org/10.1007/978-981-19-5090-2_2
https://doi.org/10.1007/978-981-19-5090-2_2
Autor:
Fathima Begum M, Subhashini Narayan
Publikováno v:
2022 Second International Conference on Next Generation Intelligent Systems (ICNGIS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5b459d3ae794b4d99f4b8270dd2a11bf
https://doi.org/10.1109/icngis54955.2022.10079856
https://doi.org/10.1109/icngis54955.2022.10079856
Autor:
subhashini narayan
Publikováno v:
Future Computing and Informatics Journal. 5:96-116
In this modern world of ever-increasing one-click purchases, movie bookings, music, healthcare, fashion, the need for recommendations have increased the more. Google, Netflix, Spotify, Amazon and other tech giants use recommendations to customize and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a93b6433acf4c195aa3237de291aec32
https://doi.org/10.54623/fue.fcij.5.2.3
https://doi.org/10.54623/fue.fcij.5.2.3
Autor:
Subhashini Narayan, E. Sathiyamoorthy
Publikováno v:
Neural Computing and Applications. 31:93-102
Recently, using of the intelligent technologies in the field of clinical decision making is increased rapidly to improve the lifestyles of patients and to help for reducing the workload and cost concerned in their healthcare. Heart diseases are one o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::45636de69e34f941c6e30d61749c287a
https://doi.org/10.1007/s00521-018-3662-3
https://doi.org/10.1007/s00521-018-3662-3
Publikováno v:
2017 3rd International Conference on Advances in Computing,Communication & Automation (ICACCA) (Fall).
Wireless sensor networks (WSNs) are an emerging technology due to its huge number of applications such as military investigations and civilian scenarios. Once deployed, these networks are unprotected and unattended thereby making them prone to severa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d0cba6e036da96acbc7f2046b51deeae
https://doi.org/10.1109/icaccaf.2017.8344727
https://doi.org/10.1109/icaccaf.2017.8344727