Researchers have made a new AI model that predicts irregular heartbeats like atrial fibrillation, a common type of heart rhythm problem. It's about 80 per cent&nbsp;accurate and can give warnings 30 minutes before the irregular heartbeat starts.

This model could be put on smartphones to read data from smartwatches, helping people take action to keep their heart rhythms stable. The study has been published&nbsp;in the journal Patterns.

To develop the model, the team used&nbsp;24-hour recordings collected from 350 patients at Tongji Hospital in Wuhan, China.

Named WARN (Warning of Atrial fibRillatioN), the model relies on deep-learning, a form of machine-learning AI algorithms that discern patterns from historical data to forecast outcomes. Deep-learning is distinguished by its multi-layered decision-making process.

<h2>Understanding this technology</h2>

The researchers observed that WARN issued advance alerts, typically 30 minutes ahead of atrial fibrillation onset, marking it as the initial method to offer warnings significantly prior to the event, they remarked.

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"We used heart rate data to train a deep learning model that can recognise different phases -- (normal) sinus rhythm, pre-atrial fibrillation and atrial fibrillation -- and calculate a 'probability of danger' that the patient will have an imminent episode," Jorge Goncalves, from the Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, and the study's corresponding author, said.

Goncalves mentioned that as atrial fibrillation approaches, the likelihood steadily rises until it surpasses a predefined threshold, triggering an early warning.

The researchers noted that due to its low computational requirements, the AI model is "well-suited for incorporation into wearable devices."

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"These devices can be used by patients on a daily basis, so our results open possibilities for the development of real-time monitoring and early warnings from comfortable wearable devices," study author Arthur Montanari, an LCSB researcher, said.

(With inputs from agencies)

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Researchers have made a new AI model that predicts irregular heartbeats like atrial fibrillation, a common type of heart rhythm problem. It's about 80 per cent accurate and can give warnings 30 minutes before the irregular heartbeat starts.

Researchers have made a new AI model that predicts irregular heartbeats like atrial fibrillation, a common type of heart rhythm problem. It's about 80 per cent accurate and can give warnings 30 minutes before the irregular heartbeat starts. This model could be put on smartphones to read data from smartwatches, helping people take action to keep their heart rhythms stable. The study has been published in the journal Patterns. To develop the model, the team used 24-hour recordings collected from 350 patients at Tongji Hospital in Wuhan, China. Named WARN (Warning of Atrial fibRillatioN), the model relies on deep-learning, a form of machine-learning AI algorithms that discern patterns from historical data to forecast outcomes. Deep-learning is distinguished by its multi-layered decision-making process. Understanding this technology The researchers observed that WARN issued advance alerts, typically 30 minutes ahead of atrial fibrillation onset, marking it as the initial method to offer warnings significantly prior to the event, they remarked. Also read | European Parliament passes first-of-its-kind artificial intelligence law "We used heart rate data to train a deep learning model that can recognise different phases -- (normal) sinus rhythm, pre-atrial fibrillation and atrial fibrillation -- and calculate a 'probability of danger' that the patient will have an imminent episode," Jorge Goncalves, from the Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, and the study's corresponding author, said. Goncalves mentioned that as atrial fibrillation approaches, the likelihood steadily rises until it surpasses a predefined threshold, triggering an early warning. The researchers noted that due to its low computational requirements, the AI model is "well-suited for incorporation into wearable devices." Also watch | Artificial Intelligence vs Hollywood actors: AI emerges as big concern in entertainment industry "These devices can be used by patients on a daily basis, so our results open possibilities for the development of real-time monitoring and early warnings from comfortable wearable devices," study author Arthur Montanari, an LCSB researcher, said. (With inputs from agencies)

This new AI model will predict cardiac irregularity 30 minutes before its onset

Researchers in Israel have come up with an artificial intelligence tool capable of analysing ECG tests and predicting heart failure with an unprecedented accuracy rate.

According to the Times of Israel, the technology is currently being used for patients who suffer from myositis — a condition which significantly increase the risk of heart failure.

The AI model was updated by feeding the data from ECG scans and medical records of 89 patients suffering from myositis between 2000 and 2020. The report claimed that the AI can understand subtle patterns in the ECGs and predict possible heart failures well ahead of time.

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Dr Shahar Shelly of Rambam Healthcare Campus, the head of the research behind the tool, told Times of Israel that this was the first AI which was built only for the patients.

“We are running ECG tests through the AI model, which sees details that doctors can’t normally detect and then predicts who is at risk of heart failure,” said Shelly.

“Given that it’s these cardiac dysfunctions that often end up killing people, this can save lives.”

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The study was conducted by Shelly and his team along with the researchers of the Cardiology Department at the prestigious US-based Mayo Clinic Medical Center.

“Further down the road, the use of this model will allow the provision of appropriate treatments at an early stage, even before the deterioration of the patients’ medical condition,” he said.

“We are talking here about preventing serious illness and even deaths.”

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Researchers in Israel have come up with an artificial intelligence tool capable of analysing ECG tests and predicting heart failure with an unprecedented accuracy rate.

Researchers in Israel have come up with an artificial intelligence tool capable of analysing ECG tests and predicting heart failure with an unprecedented accuracy rate. According to the Times of Israel, the technology is currently being used for patients who suffer from myositis — a condition which significantly increase the risk of heart failure. The AI model was updated by feeding the data from ECG scans and medical records of 89 patients suffering from myositis between 2000 and 2020. The report claimed that the AI can understand subtle patterns in the ECGs and predict possible heart failures well ahead of time. Also read | UK nurses begin unprecedented day-long strike, govt mulls law banning walkouts Dr Shahar Shelly of Rambam Healthcare Campus, the head of the research behind the tool, told Times of Israel that this was the first AI which was built only for the patients. “We are running ECG tests through the AI model, which sees details that doctors can’t normally detect and then predicts who is at risk of heart failure,” said Shelly. “Given that it’s these cardiac dysfunctions that often end up killing people, this can save lives.” Also read | EU corruption scandal: Police shares pictures of bags of cash found in raids The study was conducted by Shelly and his team along with the researchers of the Cardiology Department at the prestigious US-based Mayo Clinic Medical Center. “Further down the road, the use of this model will allow the provision of appropriate treatments at an early stage, even before the deterioration of the patients’ medical condition,” he said. “We are talking here about preventing serious illness and even deaths.”

AI tool developed in Israel can predict heart failure weeks in advance

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This new AI model will predict cardiac irregularity 30 minutes before its onset

AI tool developed in Israel can predict heart failure weeks in advance