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Machine Learning and Early Diagnosis of CVD

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Despite significant advances in the diagnosis and management of cardiac disease, cardiovascular disease continues to have high morbidity and mortality. In some cases, the diagnosis is delayed, while in others, the diagnosis is mistaken for another disorder. Advanced technology and machine learning have opened up new opportunities to evaluate image-based data. Currently, image analysis is completely reliant on observer visual assessment and using crude quantitative measures to assess cardiac function and structure. Clinicians agree that there is a need for more advanced analytical techniques that can allow for more refined quantification of imaging phenotypes.


Australian government sinks AU$19 million into AI health research projects

ZDNet

The Australian government has announced it will invest AU$19 million over three years into artificial intelligence-based health research projects designed to prevent, diagnose, and treat a range of health conditions. There are five projects in total that will receive funding as part of this announcement. The Centre for Eye Research Australia and the University of New South Wales (UNSW) will each receive nearly AU$5 million for their research projects. The Centre for Eye Research Australia has developed an AI system to detect eye and cardiovascular diseases, while UNSW is focused on using AI to understand and improve the treatment of mental health, including stress, anxiety, and depression. Another AU$7 million is being put towards two projects developed by the University of Sydney (USyd).


Paperwatch: Atrial Fibrillation and Machine Learning - FantAstrial

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In a brilliant Circulation article published last week, Siontis et al. count the ways with which machine learning could help treat atrial fibrillation. As you'll quickly find out, there are a lot of different teams out there trying different things. Atrial fibrillation (abbreviated as AF) is the most common arrhythmia in man. In AF, half of the cardiac chambers (the atria) stop contracting normally and start flailing about. In addition to the increased workload of the remaining cardiac chambers (the ventricles), AF also hugely increases the risk of stroke.


Artificial intelligence in medicine: Getting smarter one patient at a time

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By using complex algorithms to detect patterns in large datasets--like lab test results, current medications, and symptoms, to name a few--AI might actually make medicine more personable--not less. "By the time patients come in, we would already know what they've been experiencing," says Yale Medicine cardiologist and data researcher Harlan Krumholz, MD. "Especially for patients with chronic conditions, we could detect their need for medical attention before they do." The definition of AI varies among industries and even from one dictionary to another. But broadly speaking, in the realm of medicine, AI refers to the use of computer systems to create algorithms based on patterns in raw data to find connections (such as between a genetic mutation and a medical condition--or clusters of symptoms to a particular disease) that would be very hard, if not impossible, for a person to identify. To illustrate what an AI-assisted future in medicine will look like, Dr. Krumholz gives a hypothetical example of a patient at risk of heart failure, a condition where a weakened heart muscle struggles to pump enough oxygenated blood throughout the body.


Data-crunching AI in Japan predicts one's chances of developing 20 diseases

The Japan Times

Health researchers have put artificial intelligence to work in crunching big data, allowing them to develop technology that can predict the future onset of around 20 diseases so people can make preventative lifestyle changes. The model developed at Hirosaki University and Kyoto University calculates one's probability of developing a disease within three years based on data obtained from voluntary health checkups on about 20,000 people in Japan. If a patient agrees to disclose data on some 20 categories collected during checkups, the model can project the potential development of arteriosclerosis, hypertension, chronic kidney disease, osteoporosis, coronary heart disease and obesity, among other conditions. The team set up two groups of people for each disease -- those whose data suggested they could develop the ailment in the future and a control group -- and crunched their health data to predict whether would will actually develop the disease. "We made correct predictions on whether individuals will develop the diseases within three years with high accuracy," said Yasushi Okuno, professor at Kyoto University's Graduate School of Medicine.


Top Artificial Intelligence (AI) Companies 2019 and their success stories

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Artificial Intelligence (AI) is now enjoying massive acceptance from consumers and organisations worldwide. Hence, more and more companies are stepping up their game by adopting Artificial Intelligence into their functionalities. In this article, we will discuss the absolute wins of the year 2019 in terms of breakthrough AI solutions and their impact. Here are some of the AI success stories and top news for the year 2019. In May 2019, Samsung created a system that could transform facial images into a video sequence.


Machine learning will mean more drug ads, and hopefully better outcomes, says ad-tech firm DeepIntent

ZDNet

If you've ever visited a doctor, you may find yourself receiving more ads for drugs in coming years. Advertising by Big Pharma directly to consumers is a small portion of the total online advertising market but may increase as new advertising tools, some of them using machine learning, are employed by the drug companies. "Pharma is about 18% of national GPD and only 3% of digital advertising, that's pretty astonishing," Christopher Paquette, CEO of New York-based DeepIntent Technologies, told ZDNet in a telephone interview. DeepIntent, founded just over four years ago, is part of publicly traded advertising technology firm Propel Media. "There is a $20 billion opportunity to unlock this digital advertising," said Paquette.


Wearable app development trends 2020 covid

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"For one moment you have the best technology handy, the next moment it is obsolete" Technology advances every single day, we might want to believe it or not, but this moment some other technology is arising whereas some might be obsoleting. It all depends upon the moment or situation we want technology to take part in. And, there is no doubt that technology is making things a little better than yesterday. In the race of AI, AR, VR, IoT, wearable technology trends are also taking part in making the lives of people monitored and strict. Tech giant Apple came up with the concept of Apple Watches is now a competitor to other brands' smartwatches. To measure heart rate count, blood pressure monitored, steps counted, a smartwatch is more than that. When we are saying smartwatch, there is another best wearable tech that is already working as the lead role in making the lives of people counted and monitored. Wearable technology trends 2020 are taking place in people's lives and expected to reach 614.31 million units in 2025.


5 Takeaways from the AI for Healthcare Virtual Conference Udacity

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As 40% of people infected with COVID-19 are asymptomatic, if a patient is imaged for an unrelated health concern and doctors can identify COVID-19, we'll be in a much better position. In addition to identifying COVID-19 by viral detection and antibody response, we can also suspect viral infection indirectly through resting heart rate. Dr. Eric Topol explained in the "AI for Healthcare Keynote" that for a flu-like illness, the resting heart rate marker allows us to predict illness throughout the country from a wearable device like a Fitbit or Apple watch. Dr. Topol states that heart rate rises before a fever is present, so even if someone doesn't get a fever or experience symptoms, we can still detect that their body is fighting a virus. "Resting heart rate, with the analytics of AI for healthcare, can predict where an outbreak is likely to happen and that's a topic that doesn't get enough respect because people just think test, test, test and they don't understand that digital surveillance with AI can be very useful," said Dr. Topol. Pulse oximetry in wearable devices can also help us detect the virus's damage to the lungs. Dr. Topol thinks that the way to get ahead of this virus is simple: equip everyone with a wearable device that has a pulse oximeter and collects resting heart rate and body temperature. "Here we are in the US spending trillions of dollars. What we should be thinking about is: what can we arm each person with, so that we can help protect them?"


AI Tool Allows Automated ECG Interpretation for Cardiac Diagnostics

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Artificial intelligence (AI) may be an aid to interpreting ECG results, helping healthcare staff to diagnose diseases that affect the heart. Researchers at Uppsala University and heart specialists in Brazil have developed an AI that automatically diagnoses atrial fibrillation and five other common ECG abnormalities just as well as a cardiologist. The study has been published in Nature Communications. An electrocardiogram (ECG) is a simple test that can be used to check the heart's rhythm and electrical activity. The results are shown on a graph that can reveal various conditions that affect the heart.