heart attack


Could doctors use machine learning to detect heart attacks faster?

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But Dr Louise Cullen, an emergency physician at the Royal Brisbane and Women's Hospital and one of the study's authors, said there were arbitrary cut-offs for troponin levels considered to be an indicator of a heart attack. "We see people come to hospital with heart damage and high levels of troponin, some of them are having a heart attack and some have other causes," Dr Cullen said. "There's an arbitrary cut-off point for indicating a heart attack based on a so-called normal population. "The problem is we know the older you get and whether you're male or female makes a difference on what that value should be.


Could doctors use machine learning to detect heart attacks faster?

#artificialintelligence

But Dr Louise Cullen, an emergency physician at the Royal Brisbane and Women's Hospital and one of the study's authors, said there were arbitrary cut-offs for troponin levels considered to be an indicator of a heart attack. "We see people come to hospital with heart damage and high levels of troponin, some of them are having a heart attack and some have other causes," Dr Cullen said. "There's an arbitrary cut-off point for indicating a heart attack based on a so-called normal population. "The problem is we know the older you get and whether you're male or female makes a difference on what that value should be.


AI in Five, Fifty and Five Hundred Years -- Part One

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You have to step outside of your own limitations, your own beliefs, your own flawed and fragmented angle on the world and see it from a thousand different perspectives. You have to see giant abstract patterns and filter through human nature, politics, technology, social dynamics, trends, statistics and probability. It's so mind-numbingly complex that our tiny little simian brains stand very little chance of getting it right. Even predicting the future five or ten years out is amazingly complicated. So what am I going to do? Yes, I realize this is utterly insane. It's like climbing Mount Everest, with no shoes, no jacket, no Sherpa, and no oxygen after having barely climbed a small hill! Of course, I'm going to do it anyway. When someone asked George Mallory why he climbed Mt Everest, he said "because it was there." Like many famous quotes, he probably never really said it but who cares? The quote was so good we had to invent it anyway! Let's dive in and take a look at how AI will change society in the next few years, and by the time you're old and grey, and when you're long since turned to dust.


New Biomarker 'Fingerprint' with AI Technology Can Now Predict Future Heart Attacks

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Technology and AI are increasingly being used to improve our lives, especially in the medical field. Now, researchers at the University of Oxford have used machine learning to help estimate the health of arteries and have developed a new biomarker to predict heart disease, and prevent future heart attacks. The researchers claim it can identify people at risk five years before it strikes. The typical procedure for those with chest pain is to conduct CCTA or coronary CT angiogram -- an imaging test to check the arteries. "If there is no significant narrowing of the artery, which accounts for about 75 per cent of scans, people are sent home, yet some of them will still have a heart attack at some point in the future," the press release claims.


New Data Shows Artificial Intelligence Technology Can Help Doctors Better Determine Which Patients are Having a Heart Attack

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ABBOTT PARK, Ill., Sept. 12, 2019 -- Abbott announced that new research, published in the journal Circulation, found its algorithm could help doctors in hospital emergency rooms more accurately determine if someone is having a heart attack or not, so that they can receive faster treatments or be safely discharged.1 In this study, researchers from the U.S., Germany, U.K., Switzerland, Australia and New Zealand looked at more than 11,000 patients to determine if Abbott's technology developed using artificial intelligence (AI) could provide a faster, more accurate determination that someone is having a heart attack or not. The study found that the algorithm provided doctors a more comprehensive analysis of the probability that a patient was having a heart attack or not, particularly for those who entered the hospital within the first three hours of when their symptoms started. "With machine learning technology, you can go from a one-size-fits-all approach for diagnosing heart attacks to an individualized and more precise risk assessment that looks at how all the variables interact at that moment in time," said Fred Apple, Ph.D., Hennepin HealthCare/ Hennepin County Medical Center, professor of Laboratory Medicine and Pathology at the University of Minnesota, and one of the study authors. "This could give doctors in the ER more personalized, timely and accurate information to determine if their patient is having a heart attack or not." A team of physicians and statisticians at Abbott developed the algorithm* using AI tools to analyze extensive data sets and identify the variables most predictive for determining a cardiac event, such as age, sex and a person's specific troponin levels (using a high sensitivity troponin-I blood test**) and blood sample timing.


New AI technology can help diagnose heart attacks

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An algorithm combining high sensitive troponin testing with personal details can help A&E doctors better determine whether patients are having a heart attack, according to new research. The study, published in medical journal Circulation today, used Abbott's algorithm on 11,000 patients from the UK, the US, Germany, Switzerland, Australia and New Zealand, to see whether it could help deliver faster and more accurate evidence as to whether patients were suffering from a heart attack. Developed using machine learning – a branch of artificial intelligence – the algorithm uses a high sensitivity troponin-I blood test, and the time it was taken, to assess the patient's blood troponin protein levels, combining the results with personal details, such as age and sex, to deliver a bespoke assessment. It is thought this will help get around two current obstacles in heart attack diagnoses. The first is that women are currently at greater risk of misdiagnosis, because their troponin protein levels can be lower than those of men, and international guidelines for the use high sensitive troponin tests do not always account for sex in results.


AI technology can predict heart attacks University of Oxford

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Researchers have developed a heart'fingerprint' to tailor personalised treatment for people at high risk of deadly heart attack. Technology developed using artificial intelligence (AI) could identify people at high risk of a fatal heart attack at least five years before it strikes, according to new research funded by the British Heart Foundation (BHF). The findings are being presented at the European Society of Cardiology (ESC) Congress in Paris and published in the European Heart Journal. Researchers at the University of Oxford have developed a new biomarker, or'fingerprint', called the fat radiomic profile (FRP), using machine learning. The fingerprint detects biological red flags in the perivascular space lining blood vessels which supply blood to the heart.


Artificial Intelligence Can Help Doctors Better Detect Heart Attacks

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Caption: Paramedics respond to an emergency. Scientists have developed an artificial intelligence tool that lets doctors determine whether someone is having a heart attack much faster than current methods. New research published by healthcare firm Abbott shows that its algorithm could enable hospital accident and emergency departments to more accurately identify and treat patients having a cardiac arrest. The study, which involved researchers from the U.S., Germany, U.K., Switzerland, Australia and New Zealand and more than 11,000 patients, found that AI could provide doctors a more comprehensive analysis of the probability that a patient was having a heart attack. Agim Beshiri, a senior medical director at Abbott, said: "AI technology has the capability to consider many variables, characteristics and data points and combine them in seconds into meaningful results. "Because of today's advancements in computational power and AI applications, healthcare stands to benefit greatly by this approach where clinicians have to do this with their patients every day." Developed by a team of physicians and statisticians at Abbott, the algorithm uses machine learning techniques to enable a more individualized calculation of a person's heart attack risk. The technology aims to improve and quicken heart attack diagnosis by analyzing extensive datasets and identifying factors such as age, sex and a person's specific troponin levels (a cardiac biomarker). Abbott said the algorithm is designed to help address two barriers that exist today for doctors looking for more individualized information when diagnosing heart attacks. The first is that international guidelines for using highly sensitive troponin tests don't always account for personal factors, impacting test results. And the second is that while these guidelines recommend that doctors carry out troponin testing at fixed times, they don't consider a person's age or sex and put patients into a one-size-fits-all situation. However, Abbott's algorithm differs from existing approaches as it takes into consideration personal factors and troponin blood test results over time. Beshiri added: "The World Heart Organization estimates that 17.9 million people die from cardiovascular disease each year, and 85% are due to heart attacks and strokes.


Artificial Intelligence Can Help Doctors Better Detect Heart Attacks

#artificialintelligence

Caption: Paramedics respond to an emergency. Scientists have developed an artificial intelligence tool that lets doctors determine whether someone is having a heart attack much faster than current methods. New research published by healthcare firm Abbott shows that its algorithm could enable hospital accident and emergency departments to more accurately identify and treat patients having a cardiac arrest. The study, which involved researchers from the U.S., Germany, U.K., Switzerland, Australia and New Zealand and more than 11,000 patients, found that AI could provide doctors a more comprehensive analysis of the probability that a patient was having a heart attack. Agim Beshiri, a senior medical director at Abbott, said: "AI technology has the capability to consider many variables, characteristics and data points and combine them in seconds into meaningful results.


Artificial Intelligence Can Help Doctors Better Detect Heart Attacks

#artificialintelligence

Scientists have developed an artificial intelligence tool that lets doctors determine whether someone is having a heart attack much quicker than current methods. New research published by healthcare firm Abbott shows that its algorithm could enable hospital accident and emergency departments to more accurately identify and treat patients having a cardiac arrest. The study, which involved researchers from the U.S., Germany, U.K., Switzerland, Australia and New Zealand and more than 11,000 patients, found that AI could provide doctors a more comprehensive analysis of the probability that a patient was having a heart attack. Agim Beshiri, a senior medical director at Abbott, said: "AI technology has the capability to consider many variables, characteristics and data points and combine them in seconds into meaningful results. "Because of today's advancements in computational power and AI applications, healthcare stands to benefit greatly by this approach where clinicians have to do this with their patients every day." Developed by a team of physicians and statisticians at Abbott, the algorithm uses machine learning techniques to enable a more individualized calculation of a person's heart attack risk. The technology aims to improve and quicken heart attack diagnosis by analyzing extensive datasets and identifying factors such as age, sex and a person's specific troponin levels (a cardiac biomarker). Abbott said the algorithm is designed to help address two barriers that exist today for doctors looking for more individualized information when diagnosing heart attacks. The first is that international guidelines for using high sensitive troponin tests don't always account for personal factors, impacting test results. And the second is that while these guidelines recommend that doctors carry out troponin testing at fixed times, they don't consider a person's age or sex and put patients into a one-size-fits-all situation. However, Abbott's algorithm differs from existing approaches as it takes into consideration personal factors and troponin blood test results over time Beshiri added: "The World Heart Organization estimates that 17.9 million people die from cardiovascular disease each year, and 85% are due to heart attacks and strokes.