Machine learning enhanced analysis of ECG data

Even to the most seasoned human eye, the electrocardiogram (ECG), the oldest cardiological instrument, still contains hidden information.

Deepening patient cardiological syndromes will be accomplished through AI-enhanced ECG analysis.

For instance, neural networks will be used to improve risk stratification, especially in asymptomatic patients who frequently fall into a "grey-zone" where incorrect classification of a patient's propensity for arrhythmia could lead to early death.

The introduction and ongoing improvement of AI techniques pave the way for cutting-edge methods of electrocardiogram (ECG) analysis.

In this way, the ECG of patients still has hidden prognostic information that is not immediately visible to the human eye but may be important for understanding cardiac syndrome.

Link:

Erc Sector:

  • PE7_7 Signal processing
  • LS7_9: Health services, health care research
  • PE6_11: Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)

Keywords:

  • Neural networks
  • Electrocardiography machine learning
  • Telemedicine

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