Agibetov, A.; Seirer, B.; Dachs, T.-M.; Koschutnik, M.; Dalos, D.; Rettl, R.; Duca, F.; Schrutka, L.; Agis, H.; Kain, R.;
et al. Machine Learning Enables Prediction of Cardiac Amyloidosis by Routine Laboratory Parameters: A Proof-of-Concept Study. J. Clin. Med. 2020, 9, 1334.
https://doi.org/10.3390/jcm9051334
AMA Style
Agibetov A, Seirer B, Dachs T-M, Koschutnik M, Dalos D, Rettl R, Duca F, Schrutka L, Agis H, Kain R,
et al. Machine Learning Enables Prediction of Cardiac Amyloidosis by Routine Laboratory Parameters: A Proof-of-Concept Study. Journal of Clinical Medicine. 2020; 9(5):1334.
https://doi.org/10.3390/jcm9051334
Chicago/Turabian Style
Agibetov, Asan, Benjamin Seirer, Theresa-Marie Dachs, Matthias Koschutnik, Daniel Dalos, René Rettl, Franz Duca, Lore Schrutka, Hermine Agis, Renate Kain,
and et al. 2020. "Machine Learning Enables Prediction of Cardiac Amyloidosis by Routine Laboratory Parameters: A Proof-of-Concept Study" Journal of Clinical Medicine 9, no. 5: 1334.
https://doi.org/10.3390/jcm9051334
APA Style
Agibetov, A., Seirer, B., Dachs, T.-M., Koschutnik, M., Dalos, D., Rettl, R., Duca, F., Schrutka, L., Agis, H., Kain, R., Auer-Grumbach, M., Binder, C., Mascherbauer, J., Hengstenberg, C., Samwald, M., Dorffner, G., & Bonderman, D.
(2020). Machine Learning Enables Prediction of Cardiac Amyloidosis by Routine Laboratory Parameters: A Proof-of-Concept Study. Journal of Clinical Medicine, 9(5), 1334.
https://doi.org/10.3390/jcm9051334
