RadCloud—An Artificial Intelligence-Based Research Platform Integrating Machine Learning-Based Radiomics, Deep Learning, and Data Management

Authors

  • Geng Yayuan Scientific Research Department, HY Medical Technology, B-2 Building, Dongsheng Science Park, Haidian District, Beijing, 100192, China
  • Zhang Fengyan Scientific Research Department, HY Medical Technology, B-2 Building, Dongsheng Science Park, Haidian District, Beijing, 100192, China
  • Zhang Ran Scientific Research Department, HY Medical Technology, B-2 Building, Dongsheng Science Park, Haidian District, Beijing, 100192, China
  • Chen Ying Scientific Research Department, HY Medical Technology, B-2 Building, Dongsheng Science Park, Haidian District, Beijing, 100192, China
  • Xia Yuwei Scientific Research Department, HY Medical Technology, B-2 Building, Dongsheng Science Park, Haidian District, Beijing, 100192, China
  • Wang Fang Scientific Research Department, HY Medical Technology, B-2 Building, Dongsheng Science Park, Haidian District, Beijing, 100192, China
  • Yang Xunhong Scientific Research Department, HY Medical Technology, B-2 Building, Dongsheng Science Park, Haidian District, Beijing, 100192, China
  • Zuo Panli Scientific Research Department, HY Medical Technology, B-2 Building, Dongsheng Science Park, Haidian District, Beijing, 100192, China
  • Chai Xiangfei Scientific Research Department, HY Medical Technology, B-2 Building, Dongsheng Science Park, Haidian District, Beijing, 100192, China

DOI:

https://doi.org/10.2991/jaims.d.210617.001

Keywords:

Radiomics, Machine learning, Neural network, Data management,

Abstract

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.

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Published

2021-05-05

How to Cite

1.
Yayuan G, Fengyan Z, Ran Z, Ying C, Yuwei X, Fang W, Xunhong Y, Panli Z, Xiangfei C. RadCloud—An Artificial Intelligence-Based Research Platform Integrating Machine Learning-Based Radiomics, Deep Learning, and Data Management. JAIMS [Internet]. 2021 May 5 [cited 2023 Feb. 4];2(1-2):97-102. Available from: http://oapublishing-jaims.com/jaims/article/view/70