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Published Paper Details:
ARTIFICIAL NEURAL NETWORK AND INTERNET OF THINGS (IOT)-BASED PAP TEST DIAGNOSIS
Authors
Anju Lata Agnihotri,Dr. Jitendra Sheethlani
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Keywords
Cervicogram, Colposcopic, Cervicography, Artificial Neural Network, Cytologic.
Abstract
In this paper, we suggest using a serverclient framework model that makes use of Internet of Things (IoT) technology to manage Pap smear imaging data obtained from a high-resolution magnifying lens and to categorise those images.by learning using an Artificial Neural Network (ANN)server-side computation The Internet of Things (IoT) has the potential to enhance those magnifying tools. To communicate with one another while the ANN empowers a new generationmethod for high-precision imaging grouping. We make use ofAs a contribution to our proposed plan, 917 high-goal photographs were submitted.The technique achieves a 0.8834 root mean square error and0.6643 is the connection coefficient.Cervicography, another analytic tool, provides long-term, objective documenting of both common and atypical cervical cases. To coordinate visual colposcopy amplification and aim, the projected cervicogram is nearly same. An expert can get a cervicogram and send it to a professional for evaluation. The demonstrative precision of coloscopic, cytological, and cervicographic findings was investigated in a study of 700 women. A total of 136 cases of dysplasia or cancer were investigated by coordinated biopsy in 296 women who had a typical cytologic findings. Both colposcopy and cervicographic findings were suspected in 91.1 percent of the cases; cervicography was used only in 2.9 percent of the cases, and colposcopy was used exclusively in 5.9 percent of the cases. Nine instances (2.2 percent) of dysplasia were found in 404 routinely tested individuals who had no previous odd cytologic results.
IJCRT's Publication Details
Unique Identification Number - IJCRTN020022
Paper ID - 219643
Author type - Indian Author
Page Number(s) - 199-205
Pubished in - Volume 9 | Issue 3 | March 2021
DOI (Digital Object Identifier) -
No Of Downloads - 449
Author Country - India, -, -, -, -, Science and Technology
Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
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Anju Lata Agnihotri,Dr. Jitendra Sheethlani, "ARTIFICIAL NEURAL NETWORK AND INTERNET OF THINGS (IOT)-BASED PAP TEST DIAGNOSIS", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.9, Issue 3, pp.199-205, March 2021, Available at :http://www.ijcrt.org/papers/IJCRTN020022.pdf
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