TY  - JOUR 
AU  - Sampedro-Gómez, Jesús
AU  - Dorado Díaz, Pedro Ignacio
AU  - Vicente-Palacios, Víctor
AU  - Sánchez-Puente, Antonio
AU  - Jiménez-Navarro, Manuel
AU  - San Roman, J Alberto
AU  - Galindo Villardón, Purificación
AU  - Sanchez, Pedro L
AU  - Fernández-Avilés, Francisco
PY  - 2020
SN  - 0828-282X
UR  - http://hdl.handle.net/10366/161957
AB  - [EN]Machine learning (ML) has arrived in medicine to deliver individually adapted medical care. This study sought to use ML to discriminate stent restenosis (SR) compared with existing predictive scores of SR. To develop an easily applicable model, we...
LA  - eng
PB  - Elservier
KW  - Machine Learning
KW  - Cardiología
KW  - Cardiology
KW  - Artificial intelligence
KW  - Restenosis
KW  - Stent
KW  - Prognosis
KW  - Coronary Angiography
KW  - Risk Assessment
KW  - Coronary Restenosis
KW  - Risk Factors
KW  - Humans
KW  - Coronary Artery Disease
KW  - Demography
KW  - Middle Aged
KW  - Drug-Eluting Stents
KW  - Percutaneous Coronary Intervention
TI  - Machine Learning to Predict Stent Restenosis Based on Daily Demographic, Clinical, and Angiographic Characteristics.
DO  - 10.1016/j.cjca.2020.01.027
T2  - The Canadian journal of cardiology
VL  - 36
M2  - 1624
ER  -