Recent advances have given artificial intelligence the potential to completely revolutionize the way modern medicine is practiced.
Whether we realize it or not, artificial intelligence (AI) plays a significant role in our day-to-day lives. From digital assistants like Siri and Alexa to incipient technologies like self-driving cars, we’ve already begun to entrust computers with tasks thought to be impossible for anyone but humans just a decade or two ago.
Despite lingering concerns about automation-driven job loss, a recent Forrester report indicates that AI technologies “drive faster decisions in marketing, ecommerce, product management, and other areas of business by helping close the gap from insights to action,” while also showing promise in education and software development. Consequently, the report found, investment in AI tools featuring advanced analytics and machine learning is likely to be more than 300% higher in 2017 than in 2016 across all businesses.
Though many industries stand to gain from an embrace of AI, experts and lay observers alike are paying special attention to ongoing efforts to incorporate AI technologies into one particularly critical area of any economy: the healthcare sector.
The Technology Driving Healthcare AI
Originally focused on building graphics processing units (GPUs) for the gaming market, Santa Clara-based Nvidia sees an opportunity to leverage the deep learning technologies it’s developed to drive innovation in healthcare. Kimberly Powell, the company’s Business Development Manager for Healthcare, predicts that Nvidia’s powerful deep learning systems will become increasingly common in hospitals and medical research centers.
With AI tools like Nvidia’s DGX-1, doctors and researchers are able to compare a single patient’s medical history and test results to data drawn from the records of thousands of similar patients, making it easier to spot and understand critical risk factors and offer more accurate diagnoses. A number of cutting-edge healthcare startups have even used AI for everything from the automation of X-ray analyses to the development of genetic interpretation engines capable of identifying cancer-causing mutations in a patient’s genome.
Becoming Comfortable with AI in the Doctor’s Office
Of course, no matter how advanced and precise AI technologies may be, they won’t achieve widespread adoption in the medical sphere if they fail to earn patients’ trust. PwC has found that around 25% of patients in the UK would trust a fully-automated robot with their heart surgery more than they would trust a human surgeon. While this hardly indicates universal acceptance of medical AI, the fact that one in four people are comfortable entrusting matters of their own life and death to a robot is no small insight.
In less critical circumstances, patient comfort with AI only increases. According to research conducted by enterprise information management company OpenText, 38% of British patients would trust a medical diagnosis provided by an AI system, and more than one in ten would trust such a diagnosis more than one given by their human doctor. In a similar OpenText survey, 33% of Brits believed AI is likely to deliver a diagnosis faster than a doctor, and 25% believed that diagnosis would be more accurate and reliable.
Leveraging Machine Learning to Improve Healthcare Outcomes
This research suggests that machines can — and in many cases already do — augment doctors’ caregiving in remarkable and life-saving ways. Indeed, a study published last month by researchers at the University of Nottingham discovered that AI machines are consistently better at predicting cardiovascular risk than are doctors who employ standardized medical risk models.
The study used four kinds of AI algorithms to predict which of 378,000 healthy patients would develop cardiovascular disease over the next decade. Independently of the AI systems, the patients’ general practitioners also assessed their risk for heart disease using the standard set of guidelines outlined by the American College of Cardiology (ACC). While the doctors using the ACC guidelines managed to accurately predict the onset of cardiovascular disease in 72.8% of cases, the predictions offered by the AI algorithms were between 74.5% and 76.4% correct. The highest-performing algorithm correctly predicted 7.6% more cases of cardiovascular disease than the average doctor, and researchers estimate that the use of AI diagnostics helped saved 355 lives over the course of the study.
Looking Beyond Healthcare
As Nvidia’s pivot makes clear, the deep learning and predictive analytics that facilitate accurate disease diagnoses have been maturing in a wide range of industries for some time. In fact, much of the core technology now being used to improve healthcare is part and parcel of Albert™, the world’s first truly AI-driven marketing platform.
Given Albert’s wide range of capabilities, including autonomous media buying, cross-channel execution, and autonomous audience targeting, marketers at companies of all shapes and sizes would be wise to investigate the power of AI to generate meaningful results. After all, if we’re willing to entrust matters of life and death to artificial intelligence, there’s no reason we shouldn’t entrust it to better our work as well.