OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!
If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.
Requested Article:
Quantitative analysis of abnormalities in gynecologic cytopathology with deep learning
Jing Ke, Yiqing Shen, Yizhou Lu, et al.
Laboratory Investigation (2021) Vol. 101, Iss. 4, pp. 513-524
Open Access | Times Cited: 14
Jing Ke, Yiqing Shen, Yizhou Lu, et al.
Laboratory Investigation (2021) Vol. 101, Iss. 4, pp. 513-524
Open Access | Times Cited: 14
Showing 14 citing articles:
Deep learning for computational cytology: A survey
Hao Jiang, Yanning Zhou, Yi Lin, et al.
Medical Image Analysis (2022) Vol. 84, pp. 102691-102691
Open Access | Times Cited: 75
Hao Jiang, Yanning Zhou, Yi Lin, et al.
Medical Image Analysis (2022) Vol. 84, pp. 102691-102691
Open Access | Times Cited: 75
A survey on recent trends in deep learning for nucleus segmentation from histopathology images
Anusua Basu, Pradip Senapati, Mainak Deb, et al.
Evolving Systems (2023) Vol. 15, Iss. 1, pp. 203-248
Open Access | Times Cited: 38
Anusua Basu, Pradip Senapati, Mainak Deb, et al.
Evolving Systems (2023) Vol. 15, Iss. 1, pp. 203-248
Open Access | Times Cited: 38
A Weakly Supervised Deep Learning Method for Guiding Ovarian Cancer Treatment and Identifying an Effective Biomarker
Ching‐Wei Wang, Yu‐Ching Lee, Cheng‐Chang Chang, et al.
Cancers (2022) Vol. 14, Iss. 7, pp. 1651-1651
Open Access | Times Cited: 37
Ching‐Wei Wang, Yu‐Ching Lee, Cheng‐Chang Chang, et al.
Cancers (2022) Vol. 14, Iss. 7, pp. 1651-1651
Open Access | Times Cited: 37
Gynecology Meets Big Data in the Disruptive Innovation Medical Era: State-of-Art and Future Prospects
Rola Khamisy‐Farah, Leonardo B. Furstenau, Jude Dzevela Kong, et al.
International Journal of Environmental Research and Public Health (2021) Vol. 18, Iss. 10, pp. 5058-5058
Open Access | Times Cited: 26
Rola Khamisy‐Farah, Leonardo B. Furstenau, Jude Dzevela Kong, et al.
International Journal of Environmental Research and Public Health (2021) Vol. 18, Iss. 10, pp. 5058-5058
Open Access | Times Cited: 26
Using deep learning to predict survival outcome in non-surgical cervical cancer patients based on pathological images
Kun Zhang, Kui Sun, Caiyi Zhang, et al.
Journal of Cancer Research and Clinical Oncology (2023) Vol. 149, Iss. 9, pp. 6075-6083
Open Access | Times Cited: 9
Kun Zhang, Kui Sun, Caiyi Zhang, et al.
Journal of Cancer Research and Clinical Oncology (2023) Vol. 149, Iss. 9, pp. 6075-6083
Open Access | Times Cited: 9
Artifact Detection and Restoration in Histology Images With Stain-Style and Structural Preservation
Jing Ke, Kai Liu, Yuxiang Sun, et al.
IEEE Transactions on Medical Imaging (2023) Vol. 42, Iss. 12, pp. 3487-3500
Closed Access | Times Cited: 8
Jing Ke, Kai Liu, Yuxiang Sun, et al.
IEEE Transactions on Medical Imaging (2023) Vol. 42, Iss. 12, pp. 3487-3500
Closed Access | Times Cited: 8
Effective deep learning for oral exfoliative cytology classification
Shintaro Sukegawa, Futa Tanaka, Keisuke Nakano, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 10
Shintaro Sukegawa, Futa Tanaka, Keisuke Nakano, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 10
Artificial Intelligence Applications in Cytopathology
Louis Vaickus, Darcy A. Kerr, Jaylou M. Velez Torres, et al.
Surgical pathology clinics (2024) Vol. 17, Iss. 3, pp. 521-531
Closed Access | Times Cited: 1
Louis Vaickus, Darcy A. Kerr, Jaylou M. Velez Torres, et al.
Surgical pathology clinics (2024) Vol. 17, Iss. 3, pp. 521-531
Closed Access | Times Cited: 1
Artificial intelligence assisted diagnoses of fine-needle aspiration of breast diseases: a single-center experience
Péter Fritz, R Raoufi, P Dalquen, et al.
Journal of Digital Health (2023), pp. 1-11
Open Access | Times Cited: 2
Péter Fritz, R Raoufi, P Dalquen, et al.
Journal of Digital Health (2023), pp. 1-11
Open Access | Times Cited: 2
TshFNA-Examiner:甲状腺细胞学图像的核分割和癌症评估框架
Jing Ke, Junchao Zhu, Xin Yang, et al.
Journal of Shanghai Jiaotong University (Science) (2024) Vol. 29, Iss. 6, pp. 945-957
Closed Access
Jing Ke, Junchao Zhu, Xin Yang, et al.
Journal of Shanghai Jiaotong University (Science) (2024) Vol. 29, Iss. 6, pp. 945-957
Closed Access
Automated analysis of digital medical images in cervical cancer screening: A systematic review
Leshego Ledwaba, Rakiya Saidu, Bessie Malila, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Leshego Ledwaba, Rakiya Saidu, Bessie Malila, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
A deep learning framework for predicting endometrial cancer from cytopathologic images with different staining styles
R. Wang, Qing Li, Guizhi Shi, et al.
PLoS ONE (2024) Vol. 19, Iss. 7, pp. e0306549-e0306549
Open Access
R. Wang, Qing Li, Guizhi Shi, et al.
PLoS ONE (2024) Vol. 19, Iss. 7, pp. e0306549-e0306549
Open Access
Performance of artificial intelligence for diagnosing cervical intraepithelial neoplasia and cervical cancer: a systematic review and meta-analysis
Lei Liu, Jiangang Liu, Qing Su, et al.
EClinicalMedicine (2024) Vol. 80, pp. 102992-102992
Closed Access
Lei Liu, Jiangang Liu, Qing Su, et al.
EClinicalMedicine (2024) Vol. 80, pp. 102992-102992
Closed Access
Effective deep learning for oral exfoliative cytology classification
Shintaro Sukegawa, Futa Tanaka, Keisuke Nakano, et al.
Research Square (Research Square) (2022)
Closed Access
Shintaro Sukegawa, Futa Tanaka, Keisuke Nakano, et al.
Research Square (Research Square) (2022)
Closed Access
