Literature DB >> 11268471

PAPNET-assisted primary screening of conventional cervical smears.

M Cenci1, C Nagar, A Vecchione.   

Abstract

The PAPNET System is the only device with a neural-network-based-artificial intelligence to detect and show the images of abnormal cells on the monitor to be evaluated in an interactive way. We effectively used the PAPNET in rescreening of conventional cervical smears and we detected its advantages and its disadvantages. In this paper, we report our results from PAPNET-assisted primary screening performed on 20,154 conventional smears. The smears were classified as Negative or as Review. The Negative cases were rapidly rescreened mainly near the coverslip edges, which are the slide areas not analyzed by automated devices because of focusing problems. The Review cases were fully reanalyzed by the optic microscope. In summary, 140 positive smears were detected: 57 cases showed changes due to HPV, 63 LSIL, 15 HSIL, and 5 carcinomas. Therefore, the PAPNET System was confirmed as useful in primary screening of conventional cervical samples as well as rescreening.

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Year:  2000        PMID: 11268471

Source DB:  PubMed          Journal:  Anticancer Res        ISSN: 0250-7005            Impact factor:   2.480


  7 in total

1.  PathMiner: a Web-based tool for computer-assisted diagnostics in pathology.

Authors:  Lin Yang; Oncel Tuzel; Wenjin Chen; Peter Meer; Gratian Salaru; Lauri A Goodell; David J Foran
Journal:  IEEE Trans Inf Technol Biomed       Date:  2009-01-20

2.  Classification of individual lung cancer cell lines based on DNA methylation markers: use of linear discriminant analysis and artificial neural networks.

Authors:  Alberto M Marchevsky; Jeffrey A Tsou; Ite A Laird-Offringa
Journal:  J Mol Diagn       Date:  2004-02       Impact factor: 5.568

3.  Use of artificial neural network for pretreatment verification of intensity modulation radiation therapy fields.

Authors:  Seied Rabie Mahdavi; Asieh Tavakol; Mastaneh Sanei; Seyed Hadi Molana; Farshid Arbabi; Aram Rostami; Sohrab Barimani
Journal:  Br J Radiol       Date:  2019-07-24       Impact factor: 3.039

4.  Patterns Prediction of Chemotherapy Sensitivity in Cancer Cell lines Using FTIR Spectrum, Neural Network and Principal Components Analysis.

Authors:  Rezvan Zendehdel; Ali Masoudi-Nejad; Farshad H Shirazi
Journal:  Iran J Pharm Res       Date:  2012       Impact factor: 1.696

Review 5.  Artificial Neural Networks as Decision Support Tools in Cytopathology: Past, Present, and Future.

Authors:  Abraham Pouliakis; Efrossyni Karakitsou; Niki Margari; Panagiotis Bountris; Maria Haritou; John Panayiotides; Dimitrios Koutsouris; Petros Karakitsos
Journal:  Biomed Eng Comput Biol       Date:  2016-02-18

Review 6.  Artificial neural network in diagnostic cytology.

Authors:  Pranab Dey
Journal:  Cytojournal       Date:  2022-04-02       Impact factor: 2.091

7.  Discrimination of Human Cell Lines by Infrared Spectroscopy and Mathematical Modeling.

Authors:  Rezvan Zendehdel; Farshad H Shirazi
Journal:  Iran J Pharm Res       Date:  2015       Impact factor: 1.696

  7 in total

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