The Effect Of Interpolating Low Amplitude Leads On The Inverse Reconstruction Of Cardiac Electrical Activity | 0 | 0.34 | 2021 |
Estimating the Minimal Size of Training Datasets Required for the Development of Linear ECG-Lead Transformations. | 0 | 0.34 | 2021 |
Towards Explainable Artificial Intelligence and Explanation User Interfaces to Open the 'Black Box' of Automated ECG Interpretation. | 0 | 0.34 | 2020 |
Regression Or Pseudo-Inverse - Which Method Should Be Preferred When Developing Inverse Linear Ecg-Lead Transformations? | 0 | 0.34 | 2020 |
Computational time series analysis of patient referrals to a primary percutaneous coronary intervention service. | 0 | 0.34 | 2020 |
Machine Learning to Predict 30 Days and 1-Year Mortality in STEMI and Turndown Patients | 0 | 0.34 | 2020 |
Improving The Detection Of Acute Coronary Syndrome Using Machine Learning Of Blood Biomarkers | 0 | 0.34 | 2020 |
Interpolating Low Amplitude ECG Signals Combined with Filtering According to International Standards Improves Inverse Reconstruction of Cardiac Electrical Activity. | 0 | 0.34 | 2019 |
Machine Learning Improves the Detection of Misplaced V1 and V2 Electrodes During 12-Lead Electrocardiogram Acquisition. | 0 | 0.34 | 2019 |