Juan-Salvadores, P.; Veiga, C.; Jiménez DÃaz, V.A.; Guitián González, A.; Iglesia Carreño, C.; MartÃnez Reglero, C.; Baz Alonso, J.A.; Caamaño Isorna, F.; Romo, A.I.
Using Machine Learning Techniques to Predict MACE in Very Young Acute Coronary Syndrome Patients. Diagnostics 2022, 12, 422.
https://doi.org/10.3390/diagnostics12020422
AMA Style
Juan-Salvadores P, Veiga C, Jiménez DÃaz VA, Guitián González A, Iglesia Carreño C, MartÃnez Reglero C, Baz Alonso JA, Caamaño Isorna F, Romo AI.
Using Machine Learning Techniques to Predict MACE in Very Young Acute Coronary Syndrome Patients. Diagnostics. 2022; 12(2):422.
https://doi.org/10.3390/diagnostics12020422
Chicago/Turabian Style
Juan-Salvadores, Pablo, Cesar Veiga, VÃctor Alfonso Jiménez DÃaz, Alba Guitián González, Cristina Iglesia Carreño, Cristina MartÃnez Reglero, José Antonio Baz Alonso, Francisco Caamaño Isorna, and Andrés Iñiguez Romo.
2022. "Using Machine Learning Techniques to Predict MACE in Very Young Acute Coronary Syndrome Patients" Diagnostics 12, no. 2: 422.
https://doi.org/10.3390/diagnostics12020422
APA Style
Juan-Salvadores, P., Veiga, C., Jiménez DÃaz, V. A., Guitián González, A., Iglesia Carreño, C., MartÃnez Reglero, C., Baz Alonso, J. A., Caamaño Isorna, F., & Romo, A. I.
(2022). Using Machine Learning Techniques to Predict MACE in Very Young Acute Coronary Syndrome Patients. Diagnostics, 12(2), 422.
https://doi.org/10.3390/diagnostics12020422