Grammatical Evolution for Predicting Cervical Cancer Recurrence Risk-Reference-Cited by-同舟云学术

Grammatical Evolution for Predicting Cervical Cancer Recurrence Risk

Published:2023-11-24 Issue: Volume: Page:851-859
ISSN:
Container-title:2023 13th International Conference on Information Technology in Medicine and Education (ITME)
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Author:

Zhang Lei¹,He Pei²,Chang Chi-Chang³,Ting Wen-Chien⁴

Affiliation:

1. School of Cyberspace Security, Guangzhou University,Guangzhou,People's Republic of China

2. School of Computer Science and Cyber Engineering, Guangzhou University,Guangzhou,People's Republic of China

3. School of Medical Informatics, Chung Shan Medical University & IT Office. Chung Shan Medical University Hospital, Ming Chuan University Taichung City,Department of Information Management.,Taoyuan City,Taiwan

4. Chung Shan Medical University Hospital School of Medicine. Chung Shan Medical University,Division of Colorectal Surgery,Department of Surgery,Taichung City,Taiwan

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10505440/10505183/10505511.pdf?arnumber=10505511

Reference22 articles.

1. Cancer statistics, 2023

2. Prospective surgical-pathological study of disease-free interval in patients with stage IB squamous cell carcinoma of the cervix: A Gynecologic Oncology Group study

3. Preoperative prognostic variables and the impact of postoperative adjuvant therapy on the outcomes of stage IB or II cervical carcinoma patients with or without pelvic lymph node metastases

4. Application of machine learning to predict the recurrence-proneness for cervical cancer

5. Machine learning for assisting cervical cancer diagnosis: An ensemble approach