RadCloud—An Artificial Intelligence-Based Research Platform Integrating Machine Learning-Based Radiomics, Deep Learning, and Data Management
Keywords:Radiomics, Machine learning, Neural network, Data management,
AbstractRadiomics 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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Copyright (c) 2021 Geng Yayuan, Zhang Fengyan, Zhang Ran, Chen Ying, Xia Yuwei, Wang Fang, Yang Xunhong, Zuo Panli, Chai Xiangfei
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