RadCloud—An Artificial Intelligence-Based Research Platform Integrating Machine Learning-Based Radiomics, Deep Learning, and Data Management
- 10.2991/jaims.d.210617.001How to use a DOI?
- Radiomics; Machine learning; Neural network; Data management
Radiomics and artificial intelligence (AI) are two rapidly advancing techniques in precision medicine for the purpose of disease diagnosis, prognosis, surveillance, and personalized therapy. This paper introduces RadCloud, an artificial intelligent (AI) research platform that supports clinical studies. It integrates machine learning (ML)-based radiomics, deep learning (DL), and data management to simplify AI-based research, supporting rapid introduction of AI algorithms across various medical imaging specialties to meet the ever-increasing demands of future clinical research. This platform has been successfully applied for tumor detection, biomarker identification, prognosis, and treatment effect assessment across various image modalities (MR, PET/CT, CTA, US, MG, etc.) and a variety of organs (breast, lung, kidney, liver, rectum, thyroid, bone, etc). The proposed platform has shown great potential in supporting clinical studies for precision medicine.
- © 2021 The Authors. Published by Atlantis Press B.V.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Geng Yayuan AU - Zhang Fengyan AU - Zhang Ran AU - Chen Ying AU - Xia Yuwei AU - Wang Fang AU - Yang Xunhong AU - Zuo Panli AU - Chai Xiangfei PY - 2021 DA - 2021/06/21 TI - RadCloud—An Artificial Intelligence-Based Research Platform Integrating Machine Learning-Based Radiomics, Deep Learning, and Data Management JO - Journal of Artificial Intelligence for Medical Sciences SP - 97 EP - 102 VL - 2 IS - 1-2 SN - 2666-1470 UR - https://doi.org/10.2991/jaims.d.210617.001 DO - 10.2991/jaims.d.210617.001 ID - Yayuan2021 ER -