Design and implementation of a radiomic-driven intelligent dental hospital diversion system utilizing multilabel imaging data
The main contribution of this study is to propose a new treatment process that incorporates biological multi-omics data, which reduces the workload of physicians while providing timely and accurate medical care to patients. Through comparative experiments, we demonstrate that the process is more efficient than existing processes. In addition, this intelligent triage system demonstrates high prediction accuracy in practical applications, providing new ideas and methods for biological multi-omics research.
Authors
- Yijun Wang (ORCID: https://orcid.org/0000-0002-4613-0340)
- Jiefan Liu
- Meijia Zhang (ORCID: https://orcid.org/0000-0002-7935-1748)
- Ryan Sun (ORCID: https://orcid.org/0000-0003-1176-1561)
- Qi Dong Zhao (ORCID: https://orcid.org/0000-0001-9713-1864)
- Hao Lou (ORCID: https://orcid.org/0000-0003-0148-1574)
- Changyuan Yu (ORCID: https://orcid.org/0000-0002-3185-0441)
- Yichen Li (ORCID: https://orcid.org/0000-0002-5841-5896)
- Yun Yang (ORCID: https://orcid.org/0000-0002-9893-3436)
- Huanhuan Zhang (ORCID: https://orcid.org/0000-0002-8330-0580)
- Chenyue Dai
- Yanchan Wu
- Qiang Xu (ORCID: https://orcid.org/0000-0002-1536-0565)
- Enna Cai
- Dongren Yang
- Chufan Ren
Institutions
- University of Science and Technology Liaoning (CN)
- Wenzhou University (CN)
- Wenzhou Medical University (CN)
- Quzhou University (CN)
- Xian Yang Central Hospital (CN)
- Yueqing People's Hospital (CN)
- University of Chinese Academy of Sciences (CN)
Publication Details
- Journal
- Journal of Translational Medicine
- Published
- 2024-12-20
- DOI
- https://doi.org/10.1186/s12967-024-05958-2
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.40
Funders
- Natural Science Foundation of Liaoning Province