The Food and Drug Administration last year approved its first autonomous, artificially intelligent medical device. In a decision that seemed to take a page from science fiction, the FDA gave the OK to the IDx-DR, a device that uses artificial intelligence to analyze images of the back of a patient's eye to detect if they have diabetic retinopathy. It's the first FDA-approved device to provide a screening decision without requiring a clinician to interpret the results--which means providers who aren't eye specialists, such as primary-care physicians, can rely on it to screen for the eye disease. "Today's decision permits the marketing of a novel artificial intelligence technology that can be used in a primary-care doctor's office," Dr. Malvina Eydelman, director of the division of ophthalmic and ear, nose and throat devices at the FDA's Center for Devices and Radiological Health, said at the time. "The FDA will continue to facilitate the availability of safe and effective digital health devices that may improve patient access to needed healthcare," she added.

Rayfield Byrd knows when it's time to wake up every morning. The 68-year-old Oakland, Cal., resident hears a voice from the living room offering a cheery good morning. A little after 8 a.m. each day, a small yellow robot named Mabu asks Byrd how he's doing. Byrd has Type 2 diabetes and congestive heart failure, and about three years ago, he had surgery to implant a microvalve in his heart to keep his blood flowing properly. To stay healthy, he takes four medications a day and needs to exercise regularly.

The US Food and Drug Administration (FDA) has cleared an artificial intelligence (AI) algorithm from GE Healthcare that analyzes chest x-rays for pneumothorax and helps flag suspected cases for radiologists to prioritize reading, the company announced today. The algorithm, part of a set of other quality-assurance algorithms named the Critical Care Suite, was developed to run on a GE Healthcare mobile x-ray device. The software is not yet for sale, and an outside expert expressed concern about its false positive rate. The idea for the application came from bedside clinician experience of waiting for radiologists to read chest x-rays, said Rachael Callcut, MD, MSPH, a surgeon and director of data science for the Center for Digital Health Innovation at the University of California, San Francisco. UCSF proposed developing the feature as part of a development partnership with GE Healthcare.

Last year, when the Food and Drug Administration approved an Apple Watch feature that notified users if they had an irregular heart rhythm, the information tech industry hailed it as a watershed moment in consumer-focused health care. Cardiologists, on the other hand, warned that the app could lead to privacy violations, unwarranted worrying and wasteful or even dangerous medical care. It might have been good to have an authoritative assessment of the new technology's pros and cons. But in the United States, at least, that no longer happens. In Britain, France and the European Union, government agencies examine the ethical, social and economic impact of artificial intelligence and other big new technologies used in health care and elsewhere.

WAUKESHA, Wis.--(BUSINESS WIRE)--GE Healthcare today announced the Food and Drug Administration's 510(k) clearance of Critical Care Suite, an industry-first collection of artificial intelligence (AI) algorithms embedded on a mobile X-ray device. Built in collaboration with UC San Francisco (UCSF), using GE Healthcare's Edison platform, the AI algorithms help to reduce the turn-around time it can take for radiologists to review a suspected pneumothorax, a type of collapsed lung. "X-ray – the world's oldest form of medical imaging – just got a whole lot smarter, and soon, the rest of our offerings will too," says Kieran Murphy, President & CEO, GE Healthcare. "GE Healthcare is leading the way in the creation of AI applications for diagnostic imaging and taking what was once a promise and turning it into a reality. By integrating AI into every aspect of care, we will ultimately improve patient outcomes, reduce waste and inefficiencies, and eliminate costly errors. Critical Care Suite is just the beginning."

Biotechnology, pharmaceutical, and life sciences industries are where applied artificial intelligence (AI) can greatly accelerate innovation and shorten the product development life-cycle. Developing a drug typically takes 10 to 15 years on average, with only approximately 12 percent of drugs in clinical trials ultimately gaining U.S. Food and Drug Administration (FDA) approval. In an AI milestone in life sciences, Insilico Medicine announced a new machine learning tool for drug discovery that can generate a novel molecule in days instead of years and published their findings in Nature Biotechnology on September 2, 2019. Insilico Medicine is a venture-backed start-up with multiple investors that include WuXi AppTec, Juvenescence, Peter Diamandis' BOLD Capital Partners, and Pavilion Capital. Led by CEO and Founder Alex Zhavoronkov, the company's mission is to extend longevity by applied AI solutions for drug discovery and aging research.

Biotechnology, pharmaceutical, and life sciences industries are where applied artificial intelligence (AI) can greatly accelerate innovation and shorten the product development life-cycle. Developing a drug typically takes 10 to 15 years on average, with only approximately 12 percent of drugs in clinical trials ultimately gaining U.S. Food and Drug Administration (FDA) approval. In an AI milestone in life sciences, Insilico Medicine announced a new machine learning tool for drug discovery that can generate a novel molecule in days instead of years and published their findings in Nature Biotechnology on September 2, 2019. Insilico Medicine is a venture-backed start-up with multiple investors that include WuXi AppTec, Juvenescence, Peter Diamandis' BOLD Capital Partners, and Pavilion Capital. Led by CEO and Founder Alex Zhavoronkov, the company's mission is to extend longevity by applied AI solutions for drug discovery and aging research.

These research-based efforts were seen earlier last week, as a brand new'artificial intelligence powered X-ray device' that GE Healthcare claimed could reduce the time interval in detecting a collapsed lung by a staggering factor of 32, from 8 hours to 15 minutes, was cleared by the Food and Drug Administration (FDA). GE Healthcare CEO Kieran Murphy, in an interview with CNBC, said, "The health-care industry is producing huge amounts of data from images to digital health records, we strongly believe that you have to turn that data into information and insight to improve outcomes." The device, coined the'Critical Care Suite', utilizes artificial intelligence-based algorithms to scan X-ray images and detect cases of collapsed lung. One can only assume that deep learning algorithms are put in use to identify trends and patterns in the data sets that Kieran Murphy mentions, and is assessed in its efficacy to spot recurrent themes in a new sample of data. When the AI system has reason to suspect any condition, the scan is sent off to a radiologist as a confirming measure, and as such this is another example of AI-assisted healthcare, not AI-led, as is the reasonable role of artificial intelligence given its youth in the healthcare industry.

Rajarajeshwari Kodhandapani has a dream – to screen one million people for diabetic retinopathy (DR) so they can get timely treatment and not risk going blind. She is one of the four co-founders of Artelus, along with tech veterans Vish Durga, Lalit Pant, and Pradeep Walia, who is also a serial entrepreneur. As a former business analyst, she never thought she would become an entrepreneur (though she did want to become a politician at one time). Now, she is part of Artelus, a company that builds advanced screening tools to allow doctors and hospitals to diagnose a greater number of patients in the same time for a variety of diseases. Today, she wants to reach the people they call the "forgotten billion" – those in rural areas who cannot afford healthcare.

GE Healthcare announced the Food and Drug Administration's 510(k) clearance of Critical Care Suite, a collection of artificial intelligence (AI) algorithms embedded on a mobile X-ray device. Built-in collaboration with UC San Francisco (UCSF), using GE Healthcare's Edison platform, the AI algorithms help to reduce the turn-around time it can take for radiologists to review a suspected pneumothorax, a type of collapsed lung. Additional partners in the development of Critical Care Suite include St. Luke's University Health Network, Humber River Hospital, and CARING – Mahajan Imaging – India. A prioritized "STAT" X-ray can sit waiting for up to eight hours for a radiologist's review1. However, when a patient is scanned on a device with Critical Care Suite, the system automatically analyzes the images by simultaneously searching for a pneumothorax.