Artificial Intelligence in Medicine

AI for Medical Time Series

Mittwoch, 20.03.2024

Description: As time series data are increasingly collected in medical environments, there is a strong need for signal processing and modeling techniques to analyse them. Time series data may cover different temporal scales, ranging from few milliseconds (e.g. EEG data), to minutes and days (ECG or actigraphy data), and up to months or years (e.g. response to drugs). This course will provide an overview of ways to process these data, using signal processing and machine learning or modeling tools. Topics covered will include: • Introduction to time series data (representations, stationarity, visualizations etc) • Time-frequency transformations • Supervised and unsupervised algorithms for medical time-series data • Forecasting These theoretical topics will be followed by homework exercises to provide hands-on experience with the above-mentioned techniques and their applications. Learning outcomes: - An understanding of signal processing and machine learning techniques used to analyse time series data - Experience in analyzing time series biomedical data

Dozierende(r): Athina Tzovara
20.03.2024:14:15 - 16:00
Ort:5. Etage, F502
Murtenstrasse 50

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