MDPI and ACS Style
Chauhan, S.; Monlezun, D.J.; Kim, J.w.; Goel, H.; Hanna, A.; Hoang, K.; Palaskas, N.; Lopez-Mattei, J.; Hassan, S.; Kim, P.;
et al. Fractional Flow Reserve Cardio-Oncology Effects on Inpatient Mortality, Length of Stay, and Cost Based on Malignancy Type: Machine Learning Supported Nationally Representative Case-Control Study of 30 Million Hospitalizations. Medicina 2022, 58, 859.
https://doi.org/10.3390/medicina58070859
AMA Style
Chauhan S, Monlezun DJ, Kim Jw, Goel H, Hanna A, Hoang K, Palaskas N, Lopez-Mattei J, Hassan S, Kim P,
et al. Fractional Flow Reserve Cardio-Oncology Effects on Inpatient Mortality, Length of Stay, and Cost Based on Malignancy Type: Machine Learning Supported Nationally Representative Case-Control Study of 30 Million Hospitalizations. Medicina. 2022; 58(7):859.
https://doi.org/10.3390/medicina58070859
Chicago/Turabian Style
Chauhan, Siddharth, Dominique J. Monlezun, Jin wan Kim, Harsh Goel, Alex Hanna, Kenneth Hoang, Nicolas Palaskas, Juan Lopez-Mattei, Saamir Hassan, Peter Kim,
and et al. 2022. "Fractional Flow Reserve Cardio-Oncology Effects on Inpatient Mortality, Length of Stay, and Cost Based on Malignancy Type: Machine Learning Supported Nationally Representative Case-Control Study of 30 Million Hospitalizations" Medicina 58, no. 7: 859.
https://doi.org/10.3390/medicina58070859
