Prosperi, Mattia, Boucher, Christina, Bian, Jiang, and Marini, Simone. Assessing putative bias in prediction of anti-microbial resistance from real-world genotyping data under explicit causal assumptions. Retrieved from https://par.nsf.gov/biblio/10389115. Artificial Intelligence in Medicine 130.C Web. doi:10.1016/j.artmed.2022.102326.

Prosperi, Mattia, Boucher, Christina, Bian, Jiang, & Marini, Simone. Assessing putative bias in prediction of anti-microbial resistance from real-world genotyping data under explicit causal assumptions. Artificial Intelligence in Medicine, 130 (C). Retrieved from https://par.nsf.gov/biblio/10389115. https://doi.org/10.1016/j.artmed.2022.102326

Prosperi, Mattia, Boucher, Christina, Bian, Jiang, and Marini, Simone. "Assessing putative bias in prediction of anti-microbial resistance from real-world genotyping data under explicit causal assumptions". Artificial Intelligence in Medicine 130 (C). Country unknown/Code not available. https://doi.org/10.1016/j.artmed.2022.102326. https://par.nsf.gov/biblio/10389115.

@article{osti_10389115,
place = {Country unknown/Code not available}, title = {Assessing putative bias in prediction of anti-microbial resistance from real-world genotyping data under explicit causal assumptions}, url = {https://par.nsf.gov/biblio/10389115}, DOI = {10.1016/j.artmed.2022.102326}, abstractNote = {}, journal = {Artificial Intelligence in Medicine}, volume = {130}, number = {C}, author = {Prosperi, Mattia and Boucher, Christina and Bian, Jiang and Marini, Simone}, }