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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.


Healthy heart linked with low risk of eye disease and sight loss

Daily Mail - Science & tech

Age-old advice on how to look after your heart also applies to staving off eye disease and sight loss, a new study claims. US researchers have linked good cardiovascular health from a healthy diet, regular exercise and not smoking with lower odds for ocular diseases. This includes diabetic retinopathy, a condition caused by high blood sugar levels damaging the retina that can lead to blindness and cataracts, when the lens develops cloudy patches. An eye with diabetic retinopathy - a complication of diabetes, caused by high blood sugar levels damaging the back of the eye (retina). When the lens, a small transparent disc inside your eye, develops cloudy patches.


AI Supports Hospitals And Improves Patient Experience - ICT&health

#artificialintelligence

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.


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

#artificialintelligence

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.


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

#artificialintelligence

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.