Source: Opinion: AI, privacy and APIs will mould digital health in 2020 | MobiHealthNews. Babyscripts CEO Anish Sebastian outlines major tech-driven trends to keep an eye on for the new year.
Last month saw the rollout of the latest upgrades to Amazon’s Echo speaker line: earbuds, glasses and a ring that connect to Amazon’s personal assistant Alexa. These new products are just three examples of a growing trend to incorporate technology seamlessly into our human experience, representing the ever-expanding frontiers for technology that have moved far past the smartphone.
These trends and others are going to make a big impact in the healthcare space, especially as providers, payers and consumers alike slowly but surely recognize the need to incorporate tech into their workflows to meet the growing consumer demand for digital health tools. At the same time, the data-hungry nature of these innovations is creating its own problems, driving a discussion around privacy and security that is louder and more urgent than ever.
Here are three trends to look out for in the coming year:
Artificial intelligence (AI) and machine learning (ML) are growing into themselves
It’s been quite a few years since AI has emerged from the pages of science fiction into our day-to-day reality, and the healthcare industry has provided a fertile proving ground for all aspects of its innovations. From software that analyzes medical data to identify patients for clinical trials in minutes, to software that analyzes medical images to diagnose tumors in milliseconds; from chatbots that perform administrative tasks like setting up an appointment to chatbots that empathize with human emotion and manage mental anxiety; AI in digital health has evolved by leaps and bounds.
In 2020, we will continue to see AI and ML push boundaries, while at the same time mature and settle into more defined patterns.
With the adoption of technologies like FaceID, facial recognition technology will be an important player in privacy and security — intimate concerns of the healthcare field. It can be leveraged to drastically simplify the security requirements that make multi-factor authentication a time-consuming process for healthcare professionals — on average, doctors spend 52 hours a year just logging in to EHR systems. On the patient end, this same technology has the ability to detect emotional states of patients and anticipate needs based upon them, and the success of startups like Affectiva, the brainchild of MIT graduates, shows the tremendous promise of deep learning for these patient needs.