Srinivas, Katikireddy and Kiran, Dr K V D (2021) An analysis of Human Metabolic changes in Covid-19 pandemic scenario with the use of Bio-Informatics data for Thyroid disease using Machine Learning System. In: I3CAC 2021, 7-8 June 2021, Bharath University, Chennai, India.
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Abstract
The Recent time the entire world had great experience of human mistakes with respect to environment safety and bio diversity leads to wonderful technological development along with danger symptoms of human life survival by increasing pollution levels to abnormal ranges.Covid-19 pandemic situation handling had shown the negative shade of technology development which ignores environment safety. At this pandemic Covid-19 Medical Emergency situation, Machine learning is inspired to develop an automated drug evaluation system for the patients suffering with routine illness conditions from the existing valid drug bank using a blend of clustering methods. The present pandemic disease covid-19 virus has explored the scope of Medical infrastructures to be improved world wide even in the 21st century. Tele medicine and digital health facilities to be incorporated using the Doctor, Patient, Network and relevant IT tools as the basic stakeholders to offer efficient, cost effective and better health facilities to common public. In this situation it is necessary to utilize software engineering information dependent on the physio synthetic properties and chemical hindrance properties of medication dataset given by standard medication bank storehouse derived from www.drugs.com, www.drugbank.ca and www.malacards.org. The existing grouping strategies are applied as a mix of k-implies, k-medoids, various leveled techniques and Fuzzy k-intends to decide a fitting
Item Type: | Conference or Workshop Item (Paper) |
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Uncontrolled Keywords: | machine learning medical emergency covid-19 telemedicine digital health clustering thyroid |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science QA75 Electronic computers. Computer science |
Depositing User: | EAI Editor IV |
Date Deposited: | 21 Jun 2021 08:08 |
Last Modified: | 21 Jun 2021 08:08 |
URI: | https://eprints.eudl.eu/id/eprint/3854 |