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Using artificial intelligence to predict cardiovascular disease

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An international team of researchers has developed a way to use artificial intelligence to predict the risk of a patient developing cardiovascular disease. In their paper published in the journal Nature Biological Engineering, the group describes using retinal blood vessel scans as a data-source for a deep learning system to teach it to recognize the signs of cardiovascular disease in people. For over 100 years, doctors have peered into the eyes of patients looking for changes in retinal vasculature--blood vessels in the retina that can reflect the impact of high blood pressure over a period of time. Such an impact can be an indicator of impending cardiovascular disease. Over time, medical scientists have developed instruments that allow eye doctors to get a better look at the parts of the eye most susceptible to damage from hypertension and have used them as a part of a process to diagnose patients that are likely to develop the disease. But such tools still require a medical professional to make the final call.


AI system predicts medicine's hidden powers

AITopics Original Links

Treatments for new or drug-resistant infectious diseases may already be in our medicine cabinets, say the molecular biologists responsible for developing an artificial-intelligence system that can predict unknown antibiotic properties of existing drugs. The hope is that the work will result in an armoury of new treatments that can be rushed into service when standard treatments stop being effective or new pathogens arise. "In the case of new infectious diseases, there might be no time to develop a completely new drug from the ground up," says Artem Cherkasov of the University of British Columbia, in Vancouver, Canada, who made the proposal this week at a meeting of the American Chemical Society in Boston, Massachusetts. However, if the new AI system suggests an existing drug might be an effective antibiotic, it could be quickly tested for efficacy, and then pushed into service, Cherkasov says. And because these drugs would have already been approved for use in people, they wouldn't have to go through all the clinical trials and lengthy regulatory approvals required of brand-new drugs.


Best evidence yet that Parkinson's could be autoimmune disease

New Scientist

EVIDENCE that Parkinson's disease may be an autoimmune disorder could lead to new ways to treat the illness. Parkinson's begins with abnormal clumping of a protein called synuclein in the brain. Neighbouring dopamine-producing neurons then die, causing tremors and difficulty moving. The prevailing wisdom has been that these neurons die from a toxic reaction to synuclein deposits. However, Parkinson's has been linked to some gene variants that affect how the immune system works, leading to an alternative theory that synuclein causes Parkinson's by triggering the immune system to attack the brain.


Vitamin D supplements really do reduce risk of autoimmune disease

New Scientist

Vitamin D supplements really do prevent people developing an autoimmune disease, at least for those over 50, in a study providing the first evidence of a causal link between the two. Previous studies on the effect of vitamin D on autoimmune conditions have looked at vitamin D levels in those with an autoimmune disease or in those who go on to develop one. Other studies have hinted at the supplement's beneficial effects on the immune system. "We know vitamin D does all kinds of wonderful things for the immune system in animal studies," says Karen Costenbader at the Brigham and Women's Hospital in Boston. "But we have never proven before that giving vitamin D can prevent autoimmune disease." Costenbader and her colleagues randomly split nearly 26,000 people in the US who were 50 or over into two groups, giving them either vitamin D supplements or a placebo.


Review -- A Deep Learning System for Differential Diagnosis of Skin Diseases

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(I am not an expert in biomedical field. I only present this paper in the deep learning perspective. There are still many dataset statistics and results shown in the paper, please feel free to read…