Non-invasive tumor microenvironment evaluation and treatment response prediction in gastric cancer using deep learning radiomics
2023 · Cell Reports Medicine · 95 citations
https://doi.org/10.1016/j.xcrm.2023.101146
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Shengtian Sang
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13
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15
i10-index
Shengtian Sang is an academic researcher from Stanford University. The author has contributed to research in topics: Bioinformatics and Genomic Networks & Radiomics and Machine Learning in Medical Imaging & Advanced Neural Network Applications. The author has an h-index of 13, co-authored 35 publications.
ORCID: 0000-0003-0851-9520Papers by this author
worksBiology-guided deep learning predicts prognosis and cancer immunotherapy response
2023 · Nature Communications · 84 citations
https://doi.org/10.1038/s41467-023-40890-x
A method for predicting protein complex in dynamic PPI networks
2016 · BMC Bioinformatics · 51 citations
https://doi.org/10.1186/s12859-016-1101-y
Relation path feature embedding based convolutional neural network method for drug discovery
2019 · BMC Medical Informatics and Decision Making · 19 citations
https://doi.org/10.1186/s12911-019-0764-5
Biology-aware mutation-based deep learning for outcome prediction of cancer immunotherapy with immune checkpoint inhibitors
2023 · npj Precision Oncology · 8 citations
https://doi.org/10.1038/s41698-023-00468-8
Additional file 2: of A method for predicting protein complex in dynamic PPI networks
2016 · Figshare · 0 citations
https://doi.org/10.6084/m9.figshare.c.3641855_d2
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