Identification of Intracranial Germ Cell Tumors Based on Facial Photos: Exploratory Study on the Use of Deep Learning for Software Development
GVisageNet, capable of high accuracy both independently and with clinical data, shows substantial potential for early iGCTs detection, highlighting the importance of combining deep learning with clinical insights for personalized health care.
Authors
- Yanong Li (ORCID: https://orcid.org/0000-0001-8121-3777)
- Xiaoguang Qiu (ORCID: https://orcid.org/0000-0002-6806-9827)
- B. L. Wang (ORCID: https://orcid.org/0000-0003-3954-6513)
- Bo Li (ORCID: https://orcid.org/0000-0001-5760-5682)
- Yixuan He (ORCID: https://orcid.org/0009-0002-2681-7919)
- Yawei Liu (ORCID: https://orcid.org/0009-0007-5280-1132)
Institutions
- Capital Medical University (CN)
- Zhengzhou University (CN)
- Beijing Tian Tan Hospital (CN)
- Beijing Institute of Neurosurgery (CN)
- Beijing Luhe Hospital Affiliated to Capital Medical University (CN)
Publication Details
- Journal
- Journal of Medical Internet Research
- Published
- 2024-11-25
- DOI
- https://doi.org/10.2196/58760
- Primary Topic
- Brain Tumor Detection and Classification
- Type
- article
- Field-Weighted Citation Impact
- 0.00