215 related articles for article (PubMed ID: 34112790)
1. Hybrid AI-assistive diagnostic model permits rapid TBS classification of cervical liquid-based thin-layer cell smears.
Zhu X; Li X; Ong K; Zhang W; Li W; Li L; Young D; Su Y; Shang B; Peng L; Xiong W; Liu Y; Liao W; Xu J; Wang F; Liao Q; Li S; Liao M; Li Y; Rao L; Lin J; Shi J; You Z; Zhong W; Liang X; Han H; Zhang Y; Tang N; Hu A; Gao H; Cheng Z; Liang L; Yu W; Ding Y
Nat Commun; 2021 Jun; 12(1):3541. PubMed ID: 34112790
[TBL] [Abstract][Full Text] [Related]
2. [Application of artificial intelligence-assisted diagnosis for cervical liquid-based thin-layer cytology].
Zhu XH; Li XM; Zhang WL; Liao MM; Li Y; Wang FF; Shang B; Peng LG; Su YJ; You ZJ; Shi JY; Zhong WL; Liang XR; Liang CJ; Liang L; Liao WT; Ding YQ
Zhonghua Bing Li Xue Za Zhi; 2021 Apr; 50(4):333-338. PubMed ID: 33831990
[No Abstract] [Full Text] [Related]
3. [Health technology assessment report: Computer-assisted Pap test for cervical cancer screening].
Della Palma P; Moresco L; Giorgi Rossi P
Epidemiol Prev; 2012; 36(5 Suppl 3):e1-43. PubMed ID: 23139174
[TBL] [Abstract][Full Text] [Related]
4. Artificial intelligence-assisted cytology for detection of cervical intraepithelial neoplasia or invasive cancer: A multicenter, clinical-based, observational study.
Bao H; Bi H; Zhang X; Zhao Y; Dong Y; Luo X; Zhou D; You Z; Wu Y; Liu Z; Zhang Y; Liu J; Fang L; Wang L
Gynecol Oncol; 2020 Oct; 159(1):171-178. PubMed ID: 32814641
[TBL] [Abstract][Full Text] [Related]
5. Improving the Accuracy and Efficiency of Abnormal Cervical Squamous Cell Detection With Cytologist-in-the-Loop Artificial Intelligence.
Xue P; Xu HM; Tang HP; Weng HY; Wei HM; Wang Z; Zhang HY; Weng Y; Xu L; Li HX; Seery S; Han X; Ye H; Qiao YL; Jiang Y
Mod Pathol; 2023 Aug; 36(8):100186. PubMed ID: 37059230
[TBL] [Abstract][Full Text] [Related]
6. Cell preparation methods and criteria for sample adequacy. International Academy of Cytology Task Force summary. Diagnostic Cytology Towards the 21st Century: An International Expert Conference and Tutorial.
McGoogan E; Colgan TJ; Ramzy I; Cochand-Priollet B; Davey DD; Grohs HK; Gurley AM; Husain OA; Hutchinson ML; Knesel EA; Linder J; Mango LJ; Mitchell H; Peebles A; Reith A; Robinowitz M; Sauer T; Shida S; Solomon D; Topalidis T; Wilbur DC; Yamauchi K
Acta Cytol; 1998; 42(1):25-32. PubMed ID: 9479321
[TBL] [Abstract][Full Text] [Related]
7. DeepCyto: a hybrid framework for cervical cancer classification by using deep feature fusion of cytology images.
Shinde S; Kalbhor M; Wajire P
Math Biosci Eng; 2022 Apr; 19(7):6415-6434. PubMed ID: 35730264
[TBL] [Abstract][Full Text] [Related]
8. The artificial intelligence-assisted cytology diagnostic system in large-scale cervical cancer screening: A population-based cohort study of 0.7 million women.
Bao H; Sun X; Zhang Y; Pang B; Li H; Zhou L; Wu F; Cao D; Wang J; Turic B; Wang L
Cancer Med; 2020 Sep; 9(18):6896-6906. PubMed ID: 32697872
[TBL] [Abstract][Full Text] [Related]
9. SpinThin, a simple, inexpensive technique for preparation of thin-layer cervical cytology from liquid-based specimens: data on 791 cases.
Khalbuss WE; Rudomina D; Kauff ND; Chuang L; Melamed MR
Cancer; 2000 Jun; 90(3):135-42. PubMed ID: 10896326
[TBL] [Abstract][Full Text] [Related]
10. Multicenter masked evaluation of AutoCyte PREP thin layers with matched conventional smears. Including initial biopsy results.
Bishop JW; Bigner SH; Colgan TJ; Husain M; Howell LP; McIntosh KM; Taylor DA; Sadeghi MH
Acta Cytol; 1998; 42(1):189-97. PubMed ID: 9479339
[TBL] [Abstract][Full Text] [Related]
11. Increased detection of epithelial cell abnormalities by liquid-based gynecologic cytology preparations. A review of accumulated data.
Austin RM; Ramzy I
Acta Cytol; 1998; 42(1):178-84. PubMed ID: 9479337
[TBL] [Abstract][Full Text] [Related]
12. Neural-network-assisted analysis and microscopic rescreening in presumed negative cervical cytologic smears. A comparison.
Mango LJ; Valente PT
Acta Cytol; 1998; 42(1):227-32. PubMed ID: 9479345
[TBL] [Abstract][Full Text] [Related]
13. A review of image analysis and machine learning techniques for automated cervical cancer screening from pap-smear images.
William W; Ware A; Basaza-Ejiri AH; Obungoloch J
Comput Methods Programs Biomed; 2018 Oct; 164():15-22. PubMed ID: 30195423
[TBL] [Abstract][Full Text] [Related]
14. Adequacy of cellular material in split-sampling of cervical scrapings for routine cancer screening: an analysis of 702 smears.
Othman N; Othman NH
Malays J Pathol; 2012 Dec; 34(2):115-21. PubMed ID: 23424773
[TBL] [Abstract][Full Text] [Related]
15. Artificial intelligence-assisted fast screening cervical high grade squamous intraepithelial lesion and squamous cell carcinoma diagnosis and treatment planning.
Wang CW; Liou YA; Lin YJ; Chang CC; Chu PH; Lee YC; Wang CH; Chao TK
Sci Rep; 2021 Aug; 11(1):16244. PubMed ID: 34376717
[TBL] [Abstract][Full Text] [Related]
16. Comparing Deep Learning Models for Multi-cell Classification in Liquid- based Cervical Cytology Image.
Sornapudi S; Brown GT; Xue Z; Long R; Allen L; Antani S
AMIA Annu Symp Proc; 2019; 2019():820-827. PubMed ID: 32308878
[TBL] [Abstract][Full Text] [Related]
17. The ThinPrep Pap test. A review of clinical studies.
Linder J; Zahniser D
Acta Cytol; 1997; 41(1):30-8. PubMed ID: 9022723
[TBL] [Abstract][Full Text] [Related]
18. A screening assistance system for cervical cytology of squamous cell atypia based on a two-step combined CNN algorithm with label smoothing.
Nambu Y; Mariya T; Shinkai S; Umemoto M; Asanuma H; Sato I; Hirohashi Y; Torigoe T; Fujino Y; Saito T
Cancer Med; 2022 Jan; 11(2):520-529. PubMed ID: 34841722
[TBL] [Abstract][Full Text] [Related]
19. Deep Convolution Neural Network for Malignancy Detection and Classification in Microscopic Uterine Cervix Cell Images.
P B S; Faruqi F; K S H; Kudva R
Asian Pac J Cancer Prev; 2019 Nov; 20(11):3447-3456. PubMed ID: 31759371
[TBL] [Abstract][Full Text] [Related]
20. [New techniques in cytology: liquid milieu and thin slides].
Joris F; Richard J; Tötsch M
Rev Med Suisse Romande; 1999 Oct; 119(10):793-8. PubMed ID: 10582491
[No Abstract] [Full Text] [Related]
[Next] [New Search]
