Toward the tail end of pre-pandemic 2019, Mayo Clinic Chief Information Officer Cris Ross stood on a stage in California and declared, “This artificial intelligence stuff is real.”
Indeed, while some may argue that AI and machine learning might have been harnessed better during the early days of COVID-19, and while the risk of algorithmic bias is very real, there’s little question that artificial intelligence, evolving and maturing by the day for an array of use cases across healthcare.
Here are the most-read stories about AI during this most unusual year.
UK to use AI for COVID-19 vaccine side effects. On a day when vaccines, developed in record time, first begin to be administered in the U.S., it’s worth remembering AI’s crucial role in helping the world get to this hopefully pivotal moment.
AI algorithm IDs abnormal chest X-rays from COVID-19 patients. Machine learning has been a hugely valuable diagnostic tool as well, as illustrated by this story about a tool from cognitive computing vendor behold.ai that promises ‘instant triage” based on lung scans – offering faster diagnosis of COVID-19 patients and helping with resource allocation.
How AI use cases are evolving in the time of COVID-19. In a HIMSS20 Digital presentation, leaders from Google Cloud, Nuance and Health Data Analytics Institute shared perspective on how AI and automation were being deployed for pandemic response – from the hunt for therapeutics and vaccines to analytics to optimize revenue cycle strategies.
Microsoft launches major $40M AI for Health initiative. The company said the the five-year AI for Health (part of its $165 million AI for Good initiative) will help healthcare organizations around the world deploy with leading edge technologies in the service of three key areas: accelerating medical research, improving worldwide understanding to protect against global health crises such as COVID-19 and reducing health inequity.
How AI and machine learning are transforming clinical decision support. “Today’s digital tools only scratch the surface,” said Mayo Clinic Platform President Dr. John Halamka. “Incorporating newly developed algorithms that take advantage of machine learning, neural networks, and a variety of other types of artificial intelligence can help address many of the shortcomings of human intelligence.”
Clinical AI vendor Jvion unveils COVID Community Vulnerability Map. In the very early days of the pandemic, clinical AI company Jvion launched this intereactive map, which tracks the social determinants of health, helping identify populations down to the census-block level that are at risk for severe outcomes.
AI bias may worsen COVID-19 health disparities for people of color. An article in the Journal of the American Medical Informatics Association asserts that biased data models could further the disproportionate impact the COVID-19 pandemic is already having on people of color. “If not properly addressed, propagating these biases under the mantle of AI has the potential to exaggerate the health disparities faced by minority populations already bearing the highest disease burden,” said researchers.
The origins of AI in healthcare, and where it can help the industry now. “The intersection of medicine and AI is really not a new concept,” said Dr. Taha Kass-Hout, director of machine learning and chief medical officer at Amazon Web Services. (There were limited chatbots and other clinical applications as far back as the mid-60s.) But over the past few years, it has become ubiquitous across the healthcare ecosystem. “Today, if you’re looking at PubMed, it cites over 12,000 publications with deep learning, over 50,000 machine learning,” he said.
AI, telehealth could help address hospital workforce challenges. “Labor is the largest single cost for most hospitals, and the workforce is essential to the critical mission of providing life-saving care,” noted a January American Hospital Association report on the administrative, financial, operational and clinical uses of artificial intelligence. “Although there are challenges, there also are opportunities to improve care, motivate and re-skill staff, and modernize processes and business models that reflect the shift toward providing the right care, at the right time, in the right setting.”
AI is helping reinvent CDS, unlock COVID-19 insights at Mayo Clinic. In a HIMSS20 presentation, JohnHalamka shared some of the most promising recent clinical decision support advances at the Minnesota health system – and described how they’re informing treatment decisions for an array of different specialties and helping shape its understanding of COVID-19. “Imagine the power [of] an AI algorithm if you could make available every pathology slide that has ever been created in the history of the Mayo Clinic,” he said. “That’s something we’re certainly working on.”
Taking Stock of Progress and Looking Ahead
This December, we look back at a challenging year – and forward to what we hope is a better, stronger, more connected and resilient healthcare ecosystem.