High Quality Phenotypic Data and Machine Learning beat a Generic Risk Score in the Prediction of Mortality in Acute Coronary Syndrome

Kari Antila, Niku Oksala, Jussi A. Hernesniemi

Research output: Contribution to journal › Article › Professional

Original language	English
Pages (from-to)	29-30
Journal	ERCIM NEWS
Volume	118
Publication status	Published - 2019
Publication type	D1 Article in a trade journal

Access to Document

Cite this

Antila, K., Oksala, N., & Hernesniemi, J. A. (2019). High Quality Phenotypic Data and Machine Learning beat a Generic Risk Score in the Prediction of Mortality in Acute Coronary Syndrome. ERCIM NEWS, 118, 29-30. https://ercim-news.ercim.eu/en118/special/high-quality-phenotypic-data-and-machine-learning-beat-a-generic-risk-score-in-the-prediction-of-mortality-in-acute-coronary-syndrome

@article{44bf3884d9b84b92860674ca2f55c94c,

title = "High Quality Phenotypic Data and Machine Learning beat a Generic Risk Score in the Prediction of Mortality in Acute Coronary Syndrome",

author = "Kari Antila and Niku Oksala and Hernesniemi, \{Jussi A.\}",

year = "2019",

language = "English",

volume = "118",

pages = "29--30",

journal = "ERCIM NEWS",

issn = "0926-4981",

}

Antila, K, Oksala, N & Hernesniemi, JA 2019, 'High Quality Phenotypic Data and Machine Learning beat a Generic Risk Score in the Prediction of Mortality in Acute Coronary Syndrome', ERCIM NEWS, vol. 118, pp. 29-30. <https://ercim-news.ercim.eu/en118/special/high-quality-phenotypic-data-and-machine-learning-beat-a-generic-risk-score-in-the-prediction-of-mortality-in-acute-coronary-syndrome>