Simon, J.; Kraiński, Ł.; Karliński, M.; Niewada, M.; on behalf of the VISTA-Acute Collaboration.
Secondary Prevention of AFAIS: Deploying Traditional Regression, Machine Learning, and Deep Learning Models to Validate and Update CHA2DS2-VASc for 90-Day Recurrence. J. Clin. Med. 2025, 14, 7327.
https://doi.org/10.3390/jcm14207327
AMA Style
Simon J, Kraiński Ł, Karliński M, Niewada M, on behalf of the VISTA-Acute Collaboration.
Secondary Prevention of AFAIS: Deploying Traditional Regression, Machine Learning, and Deep Learning Models to Validate and Update CHA2DS2-VASc for 90-Day Recurrence. Journal of Clinical Medicine. 2025; 14(20):7327.
https://doi.org/10.3390/jcm14207327
Chicago/Turabian Style
Simon, Jenny, Łukasz Kraiński, Michał Karliński, Maciej Niewada, and on behalf of the VISTA-Acute Collaboration.
2025. "Secondary Prevention of AFAIS: Deploying Traditional Regression, Machine Learning, and Deep Learning Models to Validate and Update CHA2DS2-VASc for 90-Day Recurrence" Journal of Clinical Medicine 14, no. 20: 7327.
https://doi.org/10.3390/jcm14207327
APA Style
Simon, J., Kraiński, Ł., Karliński, M., Niewada, M., & on behalf of the VISTA-Acute Collaboration.
(2025). Secondary Prevention of AFAIS: Deploying Traditional Regression, Machine Learning, and Deep Learning Models to Validate and Update CHA2DS2-VASc for 90-Day Recurrence. Journal of Clinical Medicine, 14(20), 7327.
https://doi.org/10.3390/jcm14207327