Until recently, artificial intelligence (AI) and machine learning (ML) were buzzwords to most. Healthcare was no exception – characteristically slow to integrate AI and ML into its vocabulary, to say nothing of its operations and practices. It was unclear when AI arrived on the scene just how much potential it held. However, its ability to put patients in charge of their health or help prevent and treat diseases got its metaphorical foot in the door. While compiling data showed AI meeting efficiency milestones and pushing boundaries in other industries, clinicians remained rightfully steadfast in their demand for more information.
Enter 2020 and COVID-19 – healthcare has seen its potential vulnerabilities: insufficient and imprecise alert responses, challenges related to medical supply and hospital bed distribution, busy medical staff, and limited insight into treatments or cures. For these pitfalls and more, AI’s analytical perspective gave the power of data to clinicians and researchers working around the clock. Artificial intelligence has already played a useful but fragmented role in many aspects of the global fight against COVID-19: prediction modeling, screening, contact alerts, and diagnosis of the virus, as well as automated deliveries, and laboratory drug discovery and development.
To understand AI's advancements, we must first understand the tech and its founding. Artificial intelligence involves the development of computer systems able to perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making and language translation. AI in medicine goes back further than one might think – originating in 1964 with Eliza, the first chatbot. A natural language processing computer program, Eliza simulated conversation between a psychotherapist and a patient by pattern matching and substitution methodology that gave users the illusion of understanding on the part of the program. The developments of Eliza paved the way for computer scientists to bring present-day chatbots to life and understand deeper the programming required for additional applications of the technology.
Today, adoption of deep learning in various healthcare applications, namely medical imaging, disease diagnostics, drug discovery, and the use of sensors and connected devices to derive a patient's health status in real-time, are supplementing growth of the market. The emergence of AI-powered outbreak risk software to quickly and effectively detect and track disease outbreaks represents another high-value application. Increasing demand for personalized care, reduction of hospital readmissions, and the convenience offered by AI products and solutions are the key factors in patient adoption. Putting consumers in control of health and well-being is a growing trend in the healthcare industry, exampled by the sheer number of connected health entities entering the space each year. But AI’s demand is also driven by its benefit to healthcare professionals as they look to better understand the day-to-day patterns and needs of those they care for. This heightened understanding allows for improved feedback, guidance, and support to get and keep their patients healthy. With the amount of medical data in the world now estimated to double every few months, healthcare was ripe for AI’s input – even before the arrival of COVID-19.
Market growth is only expected to continue as AI adds more to its professional resume. Accelerated by COVID-19, artificial intelligence and machine learning are finally reaching the peak that its champions knew it could. Before COVID-19, analysts placed the value of the AI market at USD 45.2 B by the year 2026. Though a burgeoning area in the years leading to 2020, AI has seen unprecedented adoption in COVID-19’s era through six major growth areas: hospital workflow, wearable devices, medical imaging and diagnosis, therapy planning, virtual assistance, and – most significantly – drug discovery. The market is now estimated to reach USD 62.3 B by the end of 2020 – nearly one and a half times the prediction, six years early.
A roadmap for AI’s healthcare infusion is clearer today than it’s been for some time. Accelerated by the circumstances, the world sees beyond its AI reservations. As international players partner to stop COVID-19, the need for deep learning and its ability to process massive, multi-model data at high speeds presents one of the most far-reaching AI opportunities. Leveraging the artificial intelligence and machine learning technologies available today, experts will have managed the pandemic and opened doors to data collection and health insights for superior care delivery in an increasingly digital model. For future of healthcare and healthcare innovation conversations and further insight into revolutionary technologies like artificial intelligence and more, visit innovations.clevelandclinic.org and tune into Cleveland Clinic's Medical Innovation Summit, Transformation Tuesdays webinar series, and forthcoming Health Amplified podcast.