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Modelling Clinical Software for Implementing a RAPID Response Public Health Safety and Treatment DATA Management System for NOVEL Coronavirus-Convid 19 Pandemic

Source: AIChE
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    AIChE Member Credits 0.5
    AIChE Members $19.00
    AIChE Graduate Student Members Free
    AIChE Undergraduate Student Members Free
    Non-Members $29.00
  • Type:
    Conference Presentation
  • Conference Type:
    AIChE Annual Meeting
  • Presentation Date:
    November 19, 2020
  • Duration:
    27 minutes
  • Skill Level:
    Intermediate
  • PDHs:
    0.50

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A clinical software application has been developed for implementing a rapid response public health safety health management system for Novel Corona virus –CONVID-19 Pandemic. The clinical software developed is based on decision support system that utilizes model based artificial intelligent control neural network architecture to manage database of clinical solutions, cases, mortality rate through a search engine that patches for CONVID-19 published data and information electronically collated from internet. The clinical software was developed using neural network supervised learning based on data collated for CONVID-19 .The Decision support system (DSS) utilizes a Lyapunov stability model implemented with a Levenbergy Mar quart algorithm and a Newton Raphson numerical model subroutine training system to achieve improved performance to model disease diagnosis on Bayesian probability and fuzzy class data mimicking specific patient disease cases used to validate clinical software as a functional system to conform to core sector standards of International Electro Technical Commission -IEC61508. The modeled clinical treatment solutions for retro viral infection symptoms of hypoglycemia, cough, fever, headaches, pain, dehydration novel coronavirus co factors epidemiology and acute recurrent respiratory papillomatosis was developed in supervised learning class validated with published data from internet . To further development of the software sub programmes to simulate CONVID-19 epidemiology, a model was developed for CONVID-19 clinical manifestation akin to Human immunodeficiency virus type 1 (HIV-1) that encodes three enzymes which are required for the novel corona viral replication: reverse transcriptase, protease, and integrase (IN) affecting another immune bio marker-the corona respiratory tract . The software predicted vaccine therapeutic model derived from bio organic enriched with natural glucose and fructose co factors into the human system . This clinical programme was achieved in a software supervised preclinical trial surrogates genome (genetic) and phenome (behavioural) virtual human bioinformatics artificial intelligence modeled system. The results of findings hold prospects for a software to curtailed the novel corona virus spread within communities a short time based on preclinical surrogates’ model analysis based on data as reported by Wuhan China as reported Huang et.al DOI: http// doi.org/10.1016/so140-6736 (20) 30 83-5 through an effective clinical APP reporting system powered by Android mobile devices
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Checkout

Checkout

Do you already own this?

Pricing


Individuals

AIChE Member Credits 0.5
AIChE Members $19.00
AIChE Graduate Student Members Free
AIChE Undergraduate Student Members Free
Non-Members $29.00
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