This course explores machine learning applications in biomedical signal analysis, focusing on estimating patient age from electrocardiogram (ECG) features. Using the PTB-XL and PTB-XL+ datasets. You as a student will work with ECG-derived intervals, amplitudes, and waveform characteristics to develop predictive models. The course covers data exploration, feature analysis, model development, hyperparameter tuning, and evaluation. Students will gain practical experience in handling real-world biomedical data, interpreting model outputs, and critically assessing dataset biases and limitations.
- Professor: Pablo Gregori Huerta
- Professor: Bjørn-Jostein Singstad
- Professor: Per Strömberg
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