The computer will see you now. Artificial intelligence algorithms may soon bring the diagnostic know-how of an eye doctor to primary care offices and walk-in clinics, speeding up the detection of health problems and the start of treatment, especially in areas where specialized doctors are scarce. The first such program -- trained to spot symptoms of diabetes-related vision loss in eye images -- is pending approval by the U.S. Food and Drug Administration. While other already approved AI programs help doctors examine medical images, there's "not a specialist looking over the shoulder of [this] algorithm," says Michael Abràmoff, who founded and heads a company that developed the system under FDA review, dubbed IDx-DR. "It makes the clinical decision on its own."
Analyzing queries made to Google, Bing, and other search engines can reveal the potentially dangerous consequences of mixing prescriptions before they are known to the Food and Drug Administration (FDA), according to a new study. Such data mining could even expose medical risks that slip through clinical trials undetected. Pharmaceuticals often have side effects that go unnoticed until they're already available to the public. This is especially true of side effects that emerge when two drugs interact, largely because drug trials try to pinpoint the effects of one drug at a time. Physicians have a few ways to hunt for these hidden risks, such as reports to FDA from doctors, nurses, and patients.
Want to know what's in your genes? People in the US will soon be able to buy a genetic test that tells them how likely they are to develop 10 diseases, including late-onset Alzheimer's. The saliva-based test is being marketed by 23andMe, a company based in California. The firm already offers "spit kits" for US-based customers who want to find out about their ancestry or risk of passing on certain genetic diseases to their children. But in 2013, the Food and Drug Administration banned 23andMe from offering a test that assessed a person's genetic risk for 254 disorders and conditions.
The Sheffield Institute for Translational Neuroscience (SITraN) and AI start-up BenevolentAI have announced a potentially major breakthrough in the treatment of motor neuron disease, thanks to artificial intelligence. The groundbreaking development for the disease, also known as amyotrophic lateral sclerosis (ALS), came about as scientists from SITraN assessed the efficacy of a drug candidate proposed by BenevolentAI's AI technology. The scientists, led by Dr. Richard Mead and Dr. Laura Ferraiuolo, found there are significant and reproducible indications that the drug prevents the death of motor neurones in patient cell models, and delayed the onset of the disease in the gold standard model of ALS. SITraN is now moving to the next phase of its research, advancing the existing study and assessing the suitability and potential for clinical development. It expects to publish an abstract at the Motor Neurone Disease Association 28th International Symposium in Boston in December.