HEALTH AND WELLNESS PROMISES to be a huge area for AI in healthcare. Doing good public health, keeping people healthy at scale and carrying out preventive health have been difficult, to say the least. People have different types of diseases, different barriers to being healthy, and different habits and styles of learning and communication. If we want to reach them, we need to engage them in a way that appeals to them about their health concerns and issues, and in a way that they like and understand. This isn’t easy, which is why so many attempts have failed to date.
The promise of data, digital technologies and AI is that we can personalize at scale. We can apply AI to each individual’s data to figure out what issues they have, what barriers are keeping them from addressing those issues, and to offer solutions that are tailored to how they like to consume information or feedback that motivates them to take action. There’s hope that using AI tools to figure out what to do with data collected through passive methods will allow us to shift the playing field to improve patient health using technology and innovation.
Due to the COVID-19 pandemic, consumers have been increasingly buying connected monitoring devices, and that trend is expected to gather pace in the future. Deloitte expected there to be strong demand for wearable wellness tech this decade, with 320 million health and wellness wearables shipped to consumers throughout the world in 2020. The figure is due to hit 440 million by 2024. Meanwhile, CCS Insight says that over 1.2 billion devices will be in use by the end of 2025. It’s believed that new product launches and more demand from healthcare providers is helping to drive this growth.
People from all over the world are increasingly using smartwatches to monitor everything from their running pace to their health, with new hardware and software turning their watches into personalized health clinics. Innovation in the field is rapidly accelerating through advances in semiconductors, sensors and AI. These increasingly sophisticated devices mean that consumer wearables could become a screening tool to flag potential medical issues much earlier than ever before.
It’s becoming increasingly possible to use real-time data analysis with advanced AI algorithms to process the data coming from sensors about sleep, nutrition, exercise, blood pressure, weight and mood to provide real-time advice and coaching to patients. Ultimately, AI-powered digital health coaches could someday become a reality, incorporating various types of data and designing personalized plans for each individual before working with them over time to implement those plans. Using deep learning, we could build predictive models to determine patients’ biological ages. We could then use AI to develop different phenotypes that are more precise and which correlate with accelerated biological aging and even cognitive decline. More advanced phenotypes will allow for more personalized analysis of diet, lifestyle choices and glucose responses and have a huge impact on individuals.
