Literature DB >> 9111106

Common problems in Papanicolaou smear interpretation.

R M DeMay1.   

Abstract

No test ever invented has been as successful as the Papanicolaou smear in preventing cancer. Despite its remarkable success in cervical cancer prevention, however, the Papanicolaou smear is not a perfect test. Sampling errors account for a significant number of false-negative cases. Diagnostic errors occur in even the finest cytology laboratories. Yet, for women who develop cervical cancer, these errors pale in comparison with failure to screen patients adequately in the first place. This paper examines some of the problems that result in failure of the Papanicolaou smear to prevent cervical cancer, with an emphasis on common problems in Papanicolaou smear interpretation.

Entities:  

Mesh:

Year:  1997        PMID: 9111106

Source DB:  PubMed          Journal:  Arch Pathol Lab Med        ISSN: 0003-9985            Impact factor:   5.534


  10 in total

Review 1.  Cervical cancer screening.

Authors:  A Katz
Journal:  Can Fam Physician       Date:  1998-08       Impact factor: 3.275

2.  The effect of expert knowledge on medical search: medical experts have specialized abilities for detecting serious lesions.

Authors:  Ryoichi Nakashima; Chisaki Watanabe; Eriko Maeda; Takeharu Yoshikawa; Izuru Matsuda; Soichiro Miki; Kazuhiko Yokosawa
Journal:  Psychol Res       Date:  2014-10-01

3.  Generalized "satisfaction of search": adverse influences on dual-target search accuracy.

Authors:  Mathias S Fleck; Ehsan Samei; Stephen R Mitroff
Journal:  J Exp Psychol Appl       Date:  2010-03

4.  Enhancement of early cervical cancer diagnosis with epithelial layer analysis of fluorescence lifetime images.

Authors:  Jun Gu; Chit Yaw Fu; Beng Koon Ng; Lin Bo Liu; Soo Kim Lim-Tan; Caroline Guat Lay Lee
Journal:  PLoS One       Date:  2015-05-12       Impact factor: 3.240

5.  An automatic segmentation and classification framework for anti-nuclear antibody images.

Authors:  Chung-Chuan Cheng; Tsu-Yi Hsieh; Jin-Shiuh Taur; Yung-Fu Chen
Journal:  Biomed Eng Online       Date:  2013-12-09       Impact factor: 2.819

6.  Nominated texture based cervical cancer classification.

Authors:  Edwin Jayasingh Mariarputham; Allwin Stephen
Journal:  Comput Math Methods Med       Date:  2015-01-14       Impact factor: 2.238

7.  Automatic screening of cervical cells using block image processing.

Authors:  Meng Zhao; Aiguo Wu; Jingjing Song; Xuguo Sun; Na Dong
Journal:  Biomed Eng Online       Date:  2016-02-04       Impact factor: 2.819

8.  A Quantum Hybrid PSO Combined with Fuzzy k-NN Approach to Feature Selection and Cell Classification in Cervical Cancer Detection.

Authors:  Abdullah M Iliyasu; Chastine Fatichah
Journal:  Sensors (Basel)       Date:  2017-12-19       Impact factor: 3.576

9.  Feature analysis of cell nuclear chromatin distribution in support of cervical cytology.

Authors:  Hideki Komagata; Takaya Ichimura; Yasuka Matsuta; Masahiro Ishikawa; Kazuma Shinoda; Naoki Kobayashi; Atsushi Sasaki
Journal:  J Med Imaging (Bellingham)       Date:  2017-10-17

10.  Cytomorphological Features of Hyperchromatic Crowded Groups in Liquid-Based Cervicovaginal Cytology: A Single Institutional Experience.

Authors:  Youngeun Lee; Cheol Lee; In Ae Park; Hyoung Jin An; Haeryoung Kim
Journal:  J Pathol Transl Med       Date:  2019-09-16
  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.