Literature DB >> 11218185

Detection of false-negative Pap smears using the PAPNET system.

G M Troni1, I Cipparrone, M P Cariaggi, S Ciatto, G Miccinesi, M Zappa, M Confortini.   

Abstract

AIMS AND
BACKGROUND: False-negative cytological diagnoses represent the critical point of a screening program for early detection of cervical cancer. Computer-assisted reading using neural network technology has been suggested as a possible approach to manage the problem. The study assessed the performance and the cost-outcome ratio of computer-assisted versus conventional manual Pap smear reading.
METHODS: One thousand routine smears, seeded with 81 false-negative smears, were independently interpreted by two readers by conventional and PAPNET-assisted reading. Results of both readings were compared in terms of: a)sensitivity for false-negative smears, b)specificity, and c) cost-outcome (cost per CIN2+ lesion detected).
RESULTS: PAPNET-assisted reading showed a small increase in sensitivity only for one reader. Including the cost of PAPNET, the cost per detected lesion would be $7,543 and the cost per additional detected lesion would be $25,748.
CONCLUSIONS: The present study provides further evidence that PAPNET-assisted screening may allow the detection of a few extra cases of CIN2+ lesions with respect to conventional reading, though at a very high cost.

Entities:  

Mesh:

Year:  2000        PMID: 11218185     DOI: 10.1177/030089160008600604

Source DB:  PubMed          Journal:  Tumori        ISSN: 0300-8916


  4 in total

1.  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

2.  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 3.  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

4.  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

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.