Machine learning for myocardial infarction compared to guideline recommended diagnostic pathways

Jasper Boeddinghaus, Dimitrios Doudesis, Pedro Lopez-Ayala, Kuan Ken Lee, Luca Koechlin, Karin Wildi, Thomas Nestelberger, Raphael Borer, Òscar Miró, F. Martín-Sánchez, Ivo Strebel, Maria Rubini Gimenez, Dagmar I. Keller, Michael Christ, Anda Bularga, Ziwen L., Amy Ferry, Chris Tuck, Atul Anand, Alasdair GrayNicholas L Mills^*, Christian Mueller

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

1 Active
3 Finished

3 results

Filter

Finished
Machine learning and the diagnosis of myocardial infarction
Newby, D. & Mills, N.
MRC
1/02/21 → 31/01/23
Project: Research
Research Excellence Award Number 3
Baker, A.
UK-based charities
1/04/19 → 31/03/24
Project: Research
High-sensitivity Cardiac Troponin I and Risk Stratification of Patients with Suspected Acute Coronary Syndrome
Mills, N. & Lee, K.
UK-based charities
26/03/18 → 3/08/21
Project: Research

Machine learning for myocardial infarction compared to guideline recommended diagnostic pathways

Projects

Search results

Machine learning and the diagnosis of myocardial infarction

Research Excellence Award Number 3

High-sensitivity Cardiac Troponin I and Risk Stratification of Patients with Suspected Acute Coronary Syndrome