Kim, Ahyoung Amy, Rachid Zaim, Samir, and Subbian, Vignesh. Assessing reproducibility and veracity across machine learning techniques in biomedicine: A case study using TCGA data. Retrieved from https://par.nsf.gov/biblio/10188289. International Journal of Medical Informatics 141.C Web. doi:10.1016/j.ijmedinf.2020.104148.

Kim, Ahyoung Amy, Rachid Zaim, Samir, & Subbian, Vignesh. Assessing reproducibility and veracity across machine learning techniques in biomedicine: A case study using TCGA data. International Journal of Medical Informatics, 141 (C). Retrieved from https://par.nsf.gov/biblio/10188289. https://doi.org/10.1016/j.ijmedinf.2020.104148

Kim, Ahyoung Amy, Rachid Zaim, Samir, and Subbian, Vignesh. "Assessing reproducibility and veracity across machine learning techniques in biomedicine: A case study using TCGA data". International Journal of Medical Informatics 141 (C). Country unknown/Code not available. https://doi.org/10.1016/j.ijmedinf.2020.104148. https://par.nsf.gov/biblio/10188289.

@article{osti_10188289,
place = {Country unknown/Code not available}, title = {Assessing reproducibility and veracity across machine learning techniques in biomedicine: A case study using TCGA data}, url = {https://par.nsf.gov/biblio/10188289}, DOI = {10.1016/j.ijmedinf.2020.104148}, abstractNote = {}, journal = {International Journal of Medical Informatics}, volume = {141}, number = {C}, author = {Kim, Ahyoung Amy and Rachid Zaim, Samir and Subbian, Vignesh}, }