Ma, Jianzhu, Fong, Samson H., Luo, Yunan, Bakkenist, Christopher J., Shen, John Paul, Mourragui, Soufiane, Wessels, Lodewyk F., Hafner, Marc, Sharan, Roded, Peng, Jian, and Ideker, Trey. Few-shot learning creates predictive models of drug response that translate from high-throughput screens to individual patients. Retrieved from https://par.nsf.gov/biblio/10222113. Nature Cancer 2.2 Web. doi:10.1038/s43018-020-00169-2.

Ma, Jianzhu, Fong, Samson H., Luo, Yunan, Bakkenist, Christopher J., Shen, John Paul, Mourragui, Soufiane, Wessels, Lodewyk F., Hafner, Marc, Sharan, Roded, Peng, Jian, & Ideker, Trey. Few-shot learning creates predictive models of drug response that translate from high-throughput screens to individual patients. Nature Cancer, 2 (2). Retrieved from https://par.nsf.gov/biblio/10222113. https://doi.org/10.1038/s43018-020-00169-2

Ma, Jianzhu, Fong, Samson H., Luo, Yunan, Bakkenist, Christopher J., Shen, John Paul, Mourragui, Soufiane, Wessels, Lodewyk F., Hafner, Marc, Sharan, Roded, Peng, Jian, and Ideker, Trey. "Few-shot learning creates predictive models of drug response that translate from high-throughput screens to individual patients". Nature Cancer 2 (2). Country unknown/Code not available. https://doi.org/10.1038/s43018-020-00169-2. https://par.nsf.gov/biblio/10222113.

@article{osti_10222113,
place = {Country unknown/Code not available}, title = {Few-shot learning creates predictive models of drug response that translate from high-throughput screens to individual patients}, url = {https://par.nsf.gov/biblio/10222113}, DOI = {10.1038/s43018-020-00169-2}, abstractNote = {}, journal = {Nature Cancer}, volume = {2}, number = {2}, author = {Ma, Jianzhu and Fong, Samson H. and Luo, Yunan and Bakkenist, Christopher J. and Shen, John Paul and Mourragui, Soufiane and Wessels, Lodewyk F. and Hafner, Marc and Sharan, Roded and Peng, Jian and Ideker, Trey}, editor = {null} }