Deep learning application in prediction of cancer molecular alterations based on pathological images: a bibliographic analysis via CiteSpace
The use of DL is expected to provide a new strategy to effectively solve the current problem of time-consuming and expensive molecular pathology detection. Therefore, further research is needed to address issues, such as data quality and standardization, model interpretability, and resource and infrastructure requirements.
Authors
- Shuwen Han (ORCID: https://orcid.org/0000-0001-6180-9565)
- Qu Zhanbo
- Yuefen Pan (ORCID: https://orcid.org/0000-0001-6363-6231)
- Jian Liu (ORCID: https://orcid.org/0000-0001-5516-0157)
- Zefeng Wang (ORCID: https://orcid.org/0000-0002-5044-5150)
- Jin Liu (ORCID: https://orcid.org/0000-0002-9592-5748)
- Jian Chu
- Yu Xiaojian
Institutions
- Zhejiang Chinese Medical University (CN)
- Huzhou Normal University (CN)
- Huzhou Central Hospital (CN)
- Institut Systèmes Intelligents et de Robotique (FR)
Publication Details
- Journal
- Journal of Cancer Research and Clinical Oncology
- Published
- 2024-10-18
- DOI
- https://doi.org/10.1007/s00432-024-05992-z
- Citations
- 3
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.21