New tech automates insulin for diabetics

id=«article-body» class=«row» section=«article-body»> The Bigfoot closed-loop insulin system consists of an Abbott Freestyle Libre wearable wireless glucose monitor (not shown), a blood glucose computer (left) and an insulin pump (right) connected via a thin tube to a cannula for injection. The two main parts shown snap together in use to form a single compact unit.

CNET From the outside, diabetes may look like a simple condition to manage but it's actually a constant math test where the right answer is nebulous and the stakes range as high as death. But a new technology about to get broader commercial release could make insulin management the self-driving car of endocrinology.

People managing diabetes today can wear a wireless stick-on sensor to track blood glucose without finger sticks, and a pump to administer insulin without an injection pen or syringe. But the person remains in the loop, between the sensor and pump, managing and authorizing insulin delivery throughout their day. Closed-loop technology mostly removes the person from the process and delivers insulin to their body in a smart, real-time trickle, Глюкометры with the exception of mealtimes when a manual extra dose is still required.  

Now playing: Watch this: Hackers inspired the next big thing in diabetes 5:53 Bigfoot Biomedical is one of several startups planning to bring this tech to a broader market in 2019. Its system gets blood glucose data from an Abbott Freestyle Libre stick-on monitor. Then Bigfoot's proprietary smart pump calculates and Глюкометры delivers an appropriate trickle of insulin through the day via a thin tube and a small wearable injection patch. It's a lot of paraphernalia, but people who need to administer insulin are used to that. 

The results of moving from occasional finger sticks and self-dosing to a system that delivers insulin automatically and dynamically could be dramatic for people managing diabetes: Eliminating high or low glucose swings that result from inattention, inexperience or sleep, while virtually eliminating the constant «math test» insulin calculations as well.

Bigfoot's pump module is an exercise in miniaturization, using a standard battery that doesn't need recharging and a standard cartridge (upper right) of the type of insulin required. This half of the smart pump is actually discarded after use but Bigfoot plans to offer a recycling program for it.

CNET Bigfoot is far from the only firm moving in this space, a sign that it's a vital one: Medtronic's 670G was the first closed-loop system on the market in summer of 2017, Tandem Diabetes Care is planning a launch in second half of 2019 and Tidepool is working to formalize the DIY community's Loop system in a model not unlike that which grew Linux.

The closed-loop concept began with users frustrated that managing diabetes in children, during sleep and in general was a time-consuming, Глюкометры often hit-and-miss process well into the 21st century. Nearly a decade ago some of them began to hack their own closed-loop systems and OpenAPS (Open Artificial Pancreas System) open-source software arrived about five years ago to run on a Raspberry Pi and codify closed-loop DIY hacks.

The wearable wireless sensors that all closed-loop systems use offer a less direct measure of glucose than a simple blood-drop test, and a wearable pump, line and cannula may seem a bit like Frankenstein's monster to some people. But a closed-loop revolution is coming in several areas of connected health, and Глюкометры diabetes may be a key initial battleground in adjusting consumer expectations while also driving manufacturers to make the tech more transparent.

The diabetes hacking community's slogan is #wearenotwaiting. This is a technology that shouldn't have to worry about finding a market.

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Google and Verily use AI to screen patients for diabetic eye conditions

id=«article-body» class=«row» section=«article-body»> Google and Глюкометры Verily's algorithm in use at the Aravind Eye Hospital in India.

Verily Google and Verily, Alphabet's life sciences arm, are using machine learning to screen for diabetic retinopathy (DR) and diabetic macular edema (DME), two eye conditions that can lead to blindness. The goal is to enable automated screening that can detect disease sooner and provide more people with access to screenings.

Verily, part of Google parent company Alphabet, has been working with the search giant to conduct clinical research around the world and particularly in India, where studies showed the algorithm was as good at assessing images for disease as general ophthalmologists and retinal specialists, according to a Monday blog post from the companies. The results of the research led to the «first real world clinical use of the algorithm» at Aravind Eye Hospital in Madurai, India, this year, the companies said. 

The algorithm received the CE mark, certifying that it's met safety, health and environmental protection requirements in the European Union, according to the post.

In India, several cases of DR are undiagnosed because of a shortage of more than 100,000 eye doctors and a lack of screening for 66 million diabetics, the companies said. Machine learning could help more people get appropriate screenings, according to Dr. R. Kim, chief medical officer and chief of retina services at Aravind Eye Hospital.

«By integrating Verily and Google's retinal diagnostic program into our screening process, we can improve our efficiency, giving physicians like myself more time to work closely with patients on treatment and management of their disease while increasing the volume of screenings we can perform,» Kim said in a statement. 

At Aravind Eye Hospital, technicians take an image of each eye, and the algorithm then assesses the image for DR and Глюкометры DME. The technicians get quick feedback to determine whether a patient needs to be referred to a doctor.

Aravind's vision centers provide care to remote and Глюкометры rural parts of India. Verily and Google said they believe their algorithm could help in other parts of the world with a shortage of eye doctors and a growing number of people with diabetes. The companies also recently began a study with Rajavithi Hospital in Thailand to examine the algorithm's impact in a national DR screening program. In addition, they're working with Nikon and Глюкометры its subsidiary Optos to find other areas where machine learning tools that screen for diabetic eye disease could be helpful. 

Verily was previously working on smart contact lenses embedded with sensors that could potentially help diabetics monitor their glucose levels, but put that project on hold in November. 

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