Utilization of Bioinorganic Nanodrugs and Nanomaterials for the Control of Infectious Diseases Using Deep Learning.

As one of the main causes of morbidity and mortality, viral infections have a major impact on the well-being and economics of every nation in the globe. The ability to predictably diagnose viral infections improves the provision of good healthcare as well as the control and prevention of these condi...

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Publicado en:BioMed Research International Vol. 2023; pp. 1 - 14
Autores principales: Priyadarshini, R., Abdullah, A. Sheik, Karthikeyan, K. V., Vinoth, M., Martin, Betty, Geerthik, S., Wilfred, Florin, Alyami, Nour M., Sundaram, R. S.
Formato: equations & formulas research tables/charts Journal Article
Publicado: Wiley-Blackwell 4/21/2023
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 4/21/2023
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      pub: Wiley-Blackwell
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        10.1155/2023/7464159
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        atl: Utilization of Bioinorganic Nanodrugs and Nanomaterials for the Control of Infectious Diseases Using Deep Learning.
      aug:
        au:
          Priyadarshini, R.
          Abdullah, A. Sheik
          Karthikeyan, K. V.
          Vinoth, M.
          Martin, Betty
          Geerthik, S.
          Wilfred, Florin
          Alyami, Nour M.
          Sundaram, R. S.
        affil: School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, India
      sug:
        subj:
          Deep Learning
          Communicable Diseases Prevention and Control
          Nanoparticles Utilization
          Nanomedicine Utilization
          Human
          Descriptive Statistics
          Logistic Regression
          Communicable Diseases Mortality
          Psychological Well-Being
          Nanotechnology
      ab: As one of the main causes of morbidity and mortality, viral infections have a major impact on the well-being and economics of every nation in the globe. The ability to predictably diagnose viral infections improves the provision of good healthcare as well as the control and prevention of these conditions. Nanomaterials have gained widespread usage in the medical industry recently due to the rapid advancement of nanotechnology and their exceptional chemical and physical qualities, such as their small size and synthesized surface properties. The utilization of nanoparticles for illness detection, surveillance, control, preventive, and therapy, such as the treatment of bacterial infections, is referred to as nanomedicine. Nanomedicine is a comprehensive discipline that is founded on the usage of nanotechnology for clinical objectives. Nanoparticles, which have a nanoscale dimension and exhibit highly controllable optical and physical characteristics as well as the ability to bind to a large variety of chemicals, are among the most popular nanomaterials in nanomedicine. A deep learning framework of autoencoder for categorization study on viral infections is built based on actual hospital patient history of viral infections from August 2015 to August 2020. The information comprises of 10,950 cases, comprising outpatients and inpatients, encompassing the infectious diseases. Of such 10,950 instances, training set made up 70% or 7665 instances, and testing data made up 30% or 3285 instances. The data processing was done using the presented recurrent neural network-artificial bee colony (RNN-ABC) method. Sparse data densifying processes are done through the autoencoder to enhance the system learning outcome. The suggested autoencoder system was also evaluated to other widely used models, including support vector machine, logistic regression, random forest, and Naïve Bayes. In comparison to other approaches, the study's findings demonstrate how well the suggested autoencoder model can predict viral diseases. The methods used for this research can aid in removing reported lags in current monitoring systems, hence reducing society's expenses.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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