METHODS AND SYSTEM FOR CARDIAC ARRHYTHMIA PREDICTION USING TRANSFORMER-BASED NEURAL NETWORKS

Methods and systems are provided for predicting cardiac arrhythmias based on multi-modal patient monitoring data via deep learning. In an example, a method may include predicting (510) an imminent onset of a cardiac arrhythmia in a patient (170), before the cardiac arrhythmia occurs, by analyzing pa...

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Bibliographic Details
Main Authors PATIL, Abhijit, VÄÄNÄNEN, Heikki Paavo Aukusti, PATIL, Rohan Keshav, RAVISHANKAR, Hariharan
Format Patent
LanguageEnglish
French
German
Published 26.07.2023
Subjects
DIAGNOSIS
HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA
HUMAN NECESSITIES
HYGIENE
IDENTIFICATION
INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS
MEDICAL OR VETERINARY SCIENCE
PHYSICS
SURGERY
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Summary:Methods and systems are provided for predicting cardiac arrhythmias based on multi-modal patient monitoring data via deep learning. In an example, a method may include predicting (510) an imminent onset of a cardiac arrhythmia in a patient (170), before the cardiac arrhythmia occurs, by analyzing patient monitoring data via a multi-arm deep learning model (218), outputting (514) an arrhythmia event (220) in response to the prediction, and outputting (520) a report indicating features of the patient monitoring data contributing to the prediction. In this way, the multi-arm deep learning model may predict cardiac arrhythmias before their onset.
Bibliography:Application Number: EP20230150966