Medicalgorithmics has created an AI tool for the early diagnosis of cardiac arrhythmias

The artificial intelligence system created by Medicalgorithmics can diagnose the risk of a dangerous type of cardiac arrhythmia of ventricular tachycardia before the first clinical symptoms appear in patients, the company announced as part of the summary of a two-year research project. The conclusions were presented in the periodical “Heart Rhythm O2”.

“As part of the project, the artificial intelligence system created by the company retrospectively analyzed the heart rate data of over 19,000 people. patients aged 65 years and older for the risk of ventricular tachycardia. The data was collected in the 24-hour heart rate monitoring cycle by PocketECG devices, which are part of the Medicalgorithmics technological ecosystem used in the diagnosis of heart diseases.

The analysis using artificial intelligence allowed to conclude that every fifth patient from the group of over 19 thousand. people have symptoms indicating an increased risk of developing ventricular tachycardia. Thanks to the use of AI and its predictive models, they can be monitored for diagnosis and treatment before the appearance of the first, life-threatening clinical symptoms of this type of cardiac arrhythmia.

Ventricular tachycardia (ventricular tachycardia) is a serious heart disorder characterized by rapid and irregular contractions of the ventricles. It can lead to unconsciousness, heart failure and even sudden death if not diagnosed and treated early, it was explained.

Medicalgorithmics is a high-tech company present on the market since 2005, operating in the field of non-invasive medical devices. The Group strives to become a leading provider of system and algorithmic solutions in cardiological diagnostics, in particular in the field of ECG signal analysis. The company operates in, among others, the USA and Asia. In 2014, the company moved to the main market of the Warsaw Stock Exchange from NewConnect, where it had been listed since 2011. It is included in the sWIG80 index.

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