AI Supports Hospitals And Improves Patient Experience - ICT&health

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The first wave of AI hospital tools, including voice, patient experience and remote monitoring, are relatively easy to implement and deliver care to people with limited access. More highly specialized AI solutions will require higher expenses (until scale and reimbursement broaden access) and new capabilities. In mature markets like the US and EU, hospital viability will depend on their ability to adapt to the AI Era. The 5,534 US hospitals face an existential crisis. Median operating margins plummeted from 3.4 percent in 2015 to 2.7 percent in 2016 to under 2 percent in 2017.


Detecting time-evolving phenotypic topics via tensor factorization on electronic health records: Cardiovascular disease case study

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Present a method using Tensor Factorization to find subphenotypes from longitudinal EHR. We applied this approach to 12,380 patients' 10-year PheCodes prior to CVD. We identified 14 subphenotypes and showed the progress pattern. Topics Vitamin D deficiency, Urinary infections cannot be explained by traditional risk factors. Discovering subphenotypes of complex diseases can help characterize disease cohorts for investigative studies aimed at developing better diagnoses and treatments.


Novel online health calculator using Big Data to determine risk of heart disease

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Toronto: Scientists have developed a novel online health calculator using Big Data, that can help people determine their risk of heart disease as well as their heart age. The calculator allows individuals to accurately predict their risk of hospitalisation or death from cardiovascular diseases within the next five years. For example, if their risk is five per cent, it means that five in 100 people like them will experience a serious cardiovascular event in the next five years. The calculator also provides heart age, an easy-to-understand measure of heart health. Unlike other risk prediction tools, the Cardiovascular Disease Population Risk Tool considers many factors, such as socio-demographic status, environmental influences like air pollution, health behaviours ranging from smoking status to alcohol intake to physical activity, health conditions and more.


This Big Data-Based Health Calculator Predicts Your Risk of Heart Disease

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Scientists have developed a novel online health calculator using Big Data, that can help people determine their risk of heart disease as well as their heart age. The calculator allows individuals to accurately predict their risk of hospitalization or death from cardiovascular diseases within the next five years.


Are you 'fat but fit'?

FOX News

If you're overweight but seemingly healthy otherwise, consider trying to still lose weight, as new research suggests you're likely still at risk of life-threatening ailments like heart attack and stroke. For the research, presented at the European Congress on Obesity this month, study authors aimed to learn whether people diagnosed with metabolically healthy obesity (MHO) were still at risk of cardiovascular disease, according to a news release. People with MHO are obese, but don't have the metabolic risks that typically come with obesity, like diabetes, high blood pressure, poor blood sugar control, and abnormal blood fats -- all of which are known risk factors for heart disease. A BMI of 30 or above is considered obese, while 25 to 29.9 is overweight, 18.5 to 24.9 is normal, and below 18.5 is underweight, according to the National Institutes of Health. To figure out these folks' risk, researchers reviewed the electronic health records of 3.5 million adults without heart disease in The Health Improvement Network, a U.K. general practice database, spanning 1995 to 2015.