Machine learning and artificial intelligence (AI) are two hotly discussed topics in healthcare, but many radiologists tend to fear a future in which computers replace people. But the fact is that there's an overwhelming amount of misinformation and myth about how the technology will impact radiology. Eliot Siegel, MD, chief technology officer with RadSite, addressed these issues in a Feb. "It's not unusual that I'm asked by many in radiology about whether the specialty will exist in the next few years," said Siegel, the chief of imaging services at Veterans Affairs Maryland Healthcare System. Those questions are fueled partly by AI experts like Ezekiel Emanuel, an architect of the Affordable Care Act, who suggested radiologists may be replaced by computers in the next four to five years during a 2016 keynote at the American College of Radiology annual meeting, and Geoffrey Hinton, an engineering fellow at Google and emeritus professor at the University of Toronto, who compared radiologists to Wile E. Coyote--"you're already over the edge of the cliff, but you haven't yet looked down," cited Siegel in the presentation. However, Siegel notes his background in radiology and computer science provides him with a deeper understanding of the complexities in being a radiologist, and he envisions a brighter future.

Cognoa has gained regulatory recognition for its machine learning software as a class II diagnostic medical device for autism -- meaning the digital health startup is now positioned to submit an application for full FDA clearance. It's a first but important regulatory step for a business that was founded back in 2014, and plays in a still nascent digital health space where untested'wellness' apps are far more plentiful than medical technologies with robust data to prove out the efficacy of their interventions. Discussions with the FDA started in early 2017, says Cognoa CEO Brent Vaughan, adding that it's hoping to gain full FDA clearance this year. He says the ultimate goal for the US startup is to become a standard part of domestic health insurance-covered medical provision -- and for that FDA clearance is essential to opening the doors. We first covered the Cognoa at launch in 2014 and the following year when it was still being careful to describe its technology as a screening rather than a diagnostic system.

The Food and Drug Administration has approved for marketing new decision support software that could alert doctors of a potential stroke in one of their patients. The software, which uses artificial intelligence, analyzes computed tomography results and notifies providers if findings of a stroke or potential stroke are detected. "The software device could benefit patients by notifying a specialist earlier, thereby decreasing the time to treatment," says Robert Ochs, acting deputy director for radiological health in FDA's Center for Devices and Radiological Health. The vendor is Viz.AI, born at Stanford University. Viz.AI is computer-aided triage software using an artificial intelligence algorithm to analyze images for indications associated with stroke.

True to form, artificial intelligence continues to equal and even surpass doctors in the prediction and diagnosis of condition after condition. Most of this work, however, has occurred in carefully controlled laboratory experiments, with clean databases and images acquired and reviewed by experts. Now, companies are making a concerted push to bring AI into real healthcare settings, where things are messier and far less controlled. Last year, the U.S. Food and Drug Administration (FDA) approved the first machine learning application for healthcare: The Arterys Cardio DL. It uses a deep learning algorithm to analyze MRI images of the heart.

A new broad oncology deep learning suite from the cloud-based medical imaging software solutions company Arterys Inc. was approved on Thursday, Feb. 15 for 501(k) clearance by the FDA, according to a report by Business Insider. The clearance is for Aterys new Oncology AI software aimed to advance medical imaging accuracy and consistency, according to the report. This is the fifth FDA clearance Arterys has received for its deep learning cloud-based software. Specifically, the deep learning oncology software will be able to help clinicians measure and track tumors or potential cancers in solely liver and lung magnetic resonance imaging (MRI) and computed tomography (CT) scans and apply radiological standards with ease. "The evaluation of primary and metastatic disease in the lung and liver are among the most valuable contributions of radiologists to the care of patients with cancer," said radiologist and Arterys co-founder Albert Hsiao, MD, PhD, in a prepared statement.

The FDA cleared Viz.ai's clinical support tool on Feb. 13, allowing the software that alerts clinicians to the possibility of a stroke to be marketed in the United States. The product uses an algorithm to analyze CT images of the brain and send text notifications to neurovascular specialists if a large vessel blockage is present, according to the FDA's news release. The notification would be sent at the same time a radiologist is manually reviewing the images, potentially leading to faster treatment. Timely treatment is critical in stroke, the fifth-leading cause of death in the U.S. and a major cause of disability. About 795,000 Americans have a stroke each year, according to the Centers for Disease Control and Prevention (CDC).

Particularly in hospitals with limited local resources and/or limited access to neurologic expertise, telestroke is an important tool to aid in the evaluation and treatment of potential stroke,

Two years ago, Gal Salomon's mother developed sepsis during a stay in the hospital. "It was a big hospital with a lot of patients and no one saw or understood it was happening," Salomon recalls bitterly. "We lost her after two days." So when Salomon, then a partner at Israeli venture capital firm Pitango, was introduced to Clew Medical, he knew immediately that he had to get involved. Clew develops software that uses artificial intelligence (AI) to predict which patients in a hospital's intensive care unit (ICU) are at the highest risk of imminent deterioration, and it alerts staff so they can intervene early.

If you could know the exact day you die, would you want to? The question may not be as far-fetched as you might think, thanks to a new algorithm designed to analyze digital medical records and compare them to real-time health data to calculate the risk of impending health events. The FDA cleared technology from Excel Medical, known as the WAVE Clinical Platform, is being billed as the world's first patient surveillance and predictive algorithm platform. The device was designed as an always-on remote monitoring platform that can track real-time data, such as vital signs, and use that information in conjunction with the user's medical history and family medical history to calculate the risk of a potentially fatal impending health event. So far the platform has shown the ability to predict potentially deadly events such as a heart attack or respiratory failure as early as six hours before they occur.

Embrace by Empatica is a smart watch for epilepsy management to identify convulsive seizures and send alerts to caregivers. Empatica, a Massachusetts Institute of Technology spinoff, received FDA clearance for a wristworn device that uses machine learning to alert people with epilepsy and their caregivers of a convulsive seizure and track their duration and frequency. Epilepsy affects a least 2.2 million people, according to data from the Epilepsy Foundation. Empatica's Emrace device assesses multiple indicators of a seizure, including electrodermal activity, a signal associated with fight or flight response that's used by stress researchers to quantify physiological changes related to sympathetic nervous system activity, the company statement noted. In a clinical trial of the device, 135 patients across multiple sites resided at epilepsy monitoring units with continuous monitoring with video-EEG and simultaneously wore an Empatica device.