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Abstract- Person should wear a accessories which is having a features of detecting human health condition, like smart watches, bands, small devices can be attached your body somehow, which helps us to predict heart disease, or sense of cardiac. Once he detects through that device, that human should be able to find nearby hospital the one which is having heart specialist. Next suppose worst case if that specialist is not available that person should be able to get medicine related to heart disease.
Effective patient treatment plan prediction is a complex task because using body sensor, networks generate a vast amount of data of enormous number of people that need to be stored for data analysis for dynamically predict the treatment plan for individuals. Realistic patient data from various hospitals can be managed and predicted through Machining Learning Algorithm.
Keywords:
Iot, embedded systems.
Cite Article:
"A survey on prediction of cardiac arrest using machine learning ", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 10, page no.318 - 323, October-2022, Available :http://www.ijrti.org/papers/IJRTI2210043.pdf
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000205012
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator