Cardiology/Vascular Diseases


The UAB Mix - A "high-speed Dr. House" for medical breakthroughs

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Human biology is full of surprises -- especially for drug makers. Viagra wasn't designed for erectile dysfunction. Both drugs were meant to treat cardiovascular issues (as sildenafil and minoxidil, respectively), until patients reported their sexual and follicular side effects. When his son was diagnosed with an ultra-rare disease, computer scientist Matt Might, Ph.D., kicked off a search for answers. His quest led to partnerships with researchers across the country, a White House appointment, a faculty position at Harvard, and a profile in the New Yorker.


How To Democratize Healthcare: AI Gives Everyone The Very Best Doctor

Forbes Technology

The greatest problem we have is access to care. According to the CDC, nearly 20% of adults in the United States have no regular source of healthcare. One of the places this is most stark is in lifespan -- where the wealthiest Americans have benefits from steady gains, about five years of additional longevity from 2000-2014 -- versus the poorest, for whom, during the same period, life expectancy hasn't changed at all. There are many factors that contribute to this growing divide in mortality, socioeconomic and medical -- but one of the biggest is simply not enough physicians in the right places. The best doctors and providers are drawn to similar circumstances: top hospitals, with the top tier of colleagues, in the most desirable places to live, with patients that can pay for services.


Why Artificial Intelligence is Your Future Healthcare Companion

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AI, specifically cognitive computing technologies drastically transform healthcare experience for everyone in the ecosystem: doctors, patients, nurses, care givers, healthcare professionals and organizations. The influence of AI in real-life healthcare scenario is such that, gradually, the technology will adorn the role of your healthcare friend, philosopher and guide. Prior to understanding how Artificial Intelligence influences today's healthcare landscape, it is vital to know what AI really is. The hype of Artificial Intelligence (AI) has been around since the beginning of 20th century, though its contributions to healthcare remained minimal. In a broader sense, today AI is considered as the acronym for any task that a computer can perform just as well as, if not better than, humans.


Prime Minister challenges UK to transform care through AI and data science

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We've today backed a challenge from the Prime Minister, Theresa May, to make the UK a world leader in the use of data and artificial intelligence to help transform the diagnosis and treatment of chronic diseases in the UK. Speaking in Macclesfield, the Prime Minister challenged the NHS, leading health charities and industry to accelerate progress in using Artificial Intelligence (AI) to quicken the diagnosis of conditions including heart and circulatory disease, cancer and dementia. The speech supports the Government's Industrial Strategy, which includes four Grand Challenges to put the UK at the forefront of future technologies and industries. This includes growing the artificial intelligence and data driven economy and managing an ageing society. Data science is the use of maths, statistics and computer science to get answers from large, complex data sets, while AI is the use of computer algorithms to draw conclusions from this type of data without direct human input.


Artificial intelligence can be weapon in cancer fight, PM to say

BBC News

The diagnosis of cancer and other diseases in the UK can be transformed by using artificial intelligence, Theresa May is to say. The NHS and technology companies should use AI as a "new weapon" in research, the PM will urge in a speech later. Experts say it can be used to help prevent 22,000 cancer deaths a year by 2033 while aiding the fight against heart disease, diabetes and dementia. High-skilled science jobs will also be created, Mrs May is to pledge. Speaking in Macclesfield, Mrs May will say: "Late diagnosis of otherwise treatable illnesses is one of the biggest causes of avoidable deaths.


The AI Doctor Will See You Now

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Machine-learning algorithms accomplish tasks by training on a set of data, rather than being programmed by humans. Armed with the knowledge of what worked before, the system instructs the implant to stimulate users' brains to interrupt a seizure at its onset. The innovation is part of a larger phenomenon that has big implications for how we identify and treat disease: the introduction of artificial intelligence to consumer and clinical electronics. As machines learn from at times millions of humans, doctors are gaining the ability to better identify disease and even predict it before it becomes catastrophic. As in every other area of human endeavor, the introduction of AI to medicine comes with challenges.


Researchers combine wearable technology and AI to predict the onset of health problems

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A team of Waterloo researchers found that applying artificial intelligence to the right combination of data retrieved from wearable technology may detect whether your health is failing. The study, which involved researchers from Waterloo's Faculties of Applied Health Sciences and Engineering, found that the data from wearable sensors and artificial intelligence that assesses changes in aerobic responses could one day predict whether a person is experiencing the onset of a respiratory or cardiovascular disease. "The onset of a lot of chronic diseases, including type 2 diabetes and chronic obstructive pulmonary disease, has a direct impact on our aerobic fitness," said Thomas Beltrame, who led the research while at the University of Waterloo, and is now at the Institute of Computing in University of Campinas in Brazil. "In the near future, we believe it will be possible to continuously check your health, even before you realize that you need medical help." The study monitored active, healthy men in their twenties who wore a shirt for four days that incorporated sensors for heart rate, breathing and acceleration.


The AI Doctor Will See You Now

WSJ.com: WSJD - Technology

Machine-learning algorithms accomplish tasks by training on a set of data, rather than being programmed by humans. Armed with the knowledge of what worked before, the system instructs the implant to stimulate users' brains to interrupt a seizure at its onset. The innovation is part of a larger phenomenon that has big implications for how we identify and treat disease: the introduction of artificial intelligence to consumer and clinical electronics. As machines learn from at times millions of humans, doctors are gaining the ability to better identify disease and even predict it before it becomes catastrophic. As in every other area of human endeavor, the introduction of AI to medicine comes with challenges.


AI, wearable technology collaborate to predict health problems

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Researchers from the University of Waterloo in Ontario, Canada, have developed artificial intelligence (AI) capable of using wearable-collected data to predict the onset of health problems. Findings were published Feb. 23 in the Journal of Applied Physiology. The study aimed to outline a possible foundation for wearable technology and AI could partner to predict illness. Researchers hope the technology pairing could assess changes in aerobic responses to identify the onset of respiratory or cardiovascular disease. "The onset of a lot of chronic diseases, including type 2 diabetes and chronic obstructive pulmonary disease, has a direct impact on our aerobic fitness," said first author Thomas Beltrame, of the Institute of Computing in University of Campinas in Brazil, and colleagues.


Mayo Clinic study uses AI to detect heart rhythm disorder

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An artificial intelligence algorithm is able to identify patients with congenital Long QT syndrome using limited electrocardiogram data, according to an abstract published May 10 at the Heart Rhythm Scientific Sessions conference in Boston. LQTS is a heart rhythm disorder that, if left untreated, puts patients at an increased risk for arrhythmias and sudden cardiac death. For the study, a team of researchers from Rochester, Minn.-based Mayo Clinic and AliveCor sought to determine whether AI could identify patients with congenital LQTS despite patients having a normal QTc on their EKG. The researchers applied an AI algorithm that used deep neural networks to patient data from lead I of a 12-lead EKG and evaluated whether the algorithm was able to distinguish between patients with concealed LQTS and those without the condition. The researchers found the deep neural network achieved 79 percent accuracy, along with specificity of 81 percent and sensitivity of 73 percent.