2D and 3D CT Radiomics Features Prognostic Performance Comparison in Non-Small Cell Lung Cancer
2017 · Translational Oncology · 157 citations
https://doi.org/10.1016/j.tranon.2017.08.007
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Jiangdian Song
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Jiangdian Song is an academic researcher from China Medical University. The author has contributed to research in topics: Radiomics and Machine Learning in Medical Imaging & Lung Cancer Diagnosis and Treatment & Lung Cancer Treatments and Mutations. The author has an h-index of 20, co-authored 56 publications.
ORCID: 0000-0002-3355-9930Papers by this author
worksQuantitative Biomarkers for Prediction of Epidermal Growth Factor Receptor Mutation in Non-Small Cell Lung Cancer
2017 · Translational Oncology · 120 citations
https://doi.org/10.1016/j.tranon.2017.10.012
Decoding COVID-19 pneumonia: comparison of deep learning and radiomics CT image signatures
2020 · European Journal of Nuclear Medicine and Molecular Imaging · 99 citations
https://doi.org/10.1007/s00259-020-05075-4
End-to-end automatic differentiation of the coronavirus disease 2019 (COVID-19) from viral pneumonia based on chest CT
2020 · European Journal of Nuclear Medicine and Molecular Imaging · 81 citations
https://doi.org/10.1007/s00259-020-04929-1
Non-small cell lung cancer: quantitative phenotypic analysis of CT images as a potential marker of prognosis
2016 · Scientific Reports · 44 citations
https://doi.org/10.1038/srep38282
Decoding intra-tumoral spatial heterogeneity on radiological images using the Hilbert curve
2021 · Insights into Imaging · 7 citations
https://doi.org/10.1186/s13244-021-01100-8
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