Healthcare AI solutions and the HealthTech industry in general have been revolutionizing healthcare for some time. All signs point to 2022 being another year of leaps-and-bounds progress. It’s an exciting time, with new AI healthcare automation technologies emerging and others maturing to see widespread implementation.
This is a highly technical, fast-paced field that combines cutting-edge computer science, medicine and all the ethical concerns that surround healthcare. It’s no wonder that having an AI strategy in healthcare provision has so quickly become the norm. So what are the top AI trends in healthcare for 2022?
Most AI solutions in healthcare are based on one form or another of machine learning (ML). ML allows for everything from the streamlining and automation of administrative tasks to the forecasting of health risks at the population level. Anywhere large data sets are involved, ML is either already there or not far off.
Neural networks and deep learning
Deep learning and the neural networks that make it possible take things to another level. This evolution of ML can assist in and even automate the analysis of genomic data. It’s the driving force behind precision medicine. It can aid in prescription audits and even be used to detect insurance fraud.
Some of the most exciting applications of AI technologies in healthcare are in diagnostics. Convolutional neural networks (CNNs) have been able to outperform doctors in identifying disease for years. Diagnostic tools like medical imaging and healthcare data analytics are being rapidly developed.
Digital and voice assistants
Any question of how to develop AI for healthcare has to take into account patients’ participation in the process. This is where AI-driven digital assistants come in, reducing patient-provider contact when it’s not necessary and improving its quality when it is, as well as improving medication adherence.
Patient experience with AI
Another trending use for AI technology in healthcare is focused on patient experience. Throughout the diagnostic and treatment journey, AI is used to anticipate patient needs and monitor satisfaction. It’s also invaluable in boosting patient engagement, through better patient portals, for example.
Real-time patient monitoring
AI-based digital health solutions continue to improve healthcare providers’ patient-monitoring capabilities while decreasing the associated workload. Remote patient monitoring is just one area of unprecedented growth. Mental-health chatbots provide fine-grained monitoring without being too intrusive.
AI wearables are some of the more tangible HealthTech products used in remote patient monitoring. They also have promising applications in disease prevention, quality-of-life improvement and emergency response. The ML back end of these devices couples real-time data collection with predictive modeling.
AI wearables owe their utility not only to any AI subcomponents they may have running onboard, but often to their participation in an Internet of Medical Things (IoMT). An IoMT can include a huge range of sensors and devices, doing anything from automating insulin delivery to facilitating robotic surgery.
AI solutions in healthcare span the full range of the AI spectrum—from the most basic ML components to strong AI that leverages the latest advancements in deep learning. These AI healthcare technologies are brought to bear on everything from hospital inventory management to doctors’ handwriting.
Not only is this corner of the HealthTech industry incredibly vast, it’s also one of the fastest-changing fields there is. Especially in digital health, the time from proof of concept to implementation can be dizzying. Luckily, Star has a proven track record of staying on top of, if not ahead of, these trends.