Enhancing Gastrointestinal Stromal Tumor (GIST) Diagnosis: An Improved YOLOv8 Deep Learning Approach for Precise Mitotic Detection-Reference-Cited by-同舟云学术

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Enhancing Gastrointestinal Stromal Tumor (GIST) Diagnosis: An Improved YOLOv8 Deep Learning Approach for Precise Mitotic Detection

Published:2024 Issue: Volume:12 Page:116829-116840
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Liang Haoxin¹,Li Zhichun²^ORCID,Lin Weijie³,Xie Yuheng³,Zhang Shuo⁴^ORCID,Li Zhou¹,Luo Hongyu⁵,Li Tian²^ORCID,Han Shuai¹^ORCID

Affiliation:

1. Department of General Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, China

2. Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, SAR, China

3. The Second Clinical College, Southern Medical University, Guangzhou, Guangdong, China

4. School of Instrument Science and Engineering, Southeast University, Nanjing, Jiangsu, China

5. Department of General Surgery, The Sixth People’s Hospital of Huizhou City, Huizhou, China

Funder

Guangdong Science and Technology Programme

Southern Medical University 2024 College Student Innovation Training Plan Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10640084.pdf?arnumber=10640084

Reference42 articles.

1. Global epidemiology of gastrointestinal stromal tumours (GIST): A systematic review of population-based cohort studies

2. Gastrointestinal stromal tumours: ESMO–EURACAN Clinical Practice Guidelines for diagnosis, treatment and follow-up

3. Survival Outcomes Associated With 3 Years vs 1 Year of Adjuvant Imatinib for Patients With High-Risk Gastrointestinal Stromal Tumors

4. The management of metastatic GIST: current standard and investigational therapeutics

5. New treatment strategies for advanced-stage gastrointestinal stromal tumours

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