This is the second in a series of articles on the dramatic transformation taking place in health informatics, in large part because of the new Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) standard.
With an aging population, the incidence and prevalence of wound problems is on the rise. Bedsores are painful, take months to heal, and, for many patients, never do, leading to other health problems.
According to the National Cancer Institute, 4 million people die of cancer worldwide every year—almost 500 every hour. But the most shocking thing about that statistic is this: more than a third and possibly even the vast majority of those deaths could have been prevented through sufficiently early detection. Now, a new competition aims to turn that situation around.
For Ashley Zappia, getting her hands dirty was part of her job. Even though she always tried to remain as clean as possible, her work as a nursing aide at a Southern California hospital required a lot of diapering, changing, and other hands-on tasks.
The idea is a compelling one: a device that looks and feels like an ordinary contact lens but that can continuously monitor a variety of health indicators. For a diabetic, such a lens might update blood glucose levels and, using a built-in flashing LED indicator light, signal when a condition needs attention.
Jeffrey Ardell, Founding Director of the UCLA Neurocardiology Research Program of Excellence, is a fellow of the American Heart Association and has been one of the principal investigators in the field of neurocardiology for the last three decades. IEEE Pulse recently spoke with him about the role neuromodulation will play in cardiac disease intervention.
People in advanced, industrialized countries are living longer, and chronic disease rates among the elderly are on the rise in part because of lifestyle issues As a result, the care of chronic diseases (such as hypertension, heart disease, diabetes, chronic lung disease, and chronic kidney disease) accounts for well over 90% of spending by Medicare.
Artificial intelligence (AI) and machine learning (ML) have influenced medicine in myriad ways, and medical imaging is at the forefront of technological transformation. Recent advances in AI/ML fields have made an impact on imaging and image analysis across the board, from microscopy to radiology. AI has been an active field of research since the 1950s; however, for most of this period, algorithms achieved subhuman performance and were not broadly adopted in medicine.
At first, Ahmed El-Sohemy was puzzled by his data—they were the complete opposite of what they should have been. It was supposed to be a straightforward study of cholesterol metabolism in rats and merely replicate the protocol from another, previously published study. El-Sohemy initially assumed the discrepancy had something to do with the rat chow; but, no, he had fed the rats the very same high-cholesterol feed as in the previous study, and the blood levels of cholesterol reflected that.
Mike McKenna was tired of epilepsy controlling his life. For years, he tried different medications and therapies to no avail; his seizures, which occurred every three to six days, dictated what he could do and where he could live. Then, about ten years ago, he