Role of AI in healthcare applications is more aggressive, invasive

The role of AI in healthcare until now has been limited, but it's growing in ways that show great promise in patient outcomes while augmenting -- rather than replacing -- what human healthcare providers can do.

Many of the early and effective applications are in medical imaging, where deep learning and other AI methods can spot anomalies missed by the naked eye. Indeed, radiology leads in pioneering AI applications with help from advancements in computer vision and success at detecting early signs of Alzheimer's disease in brain scans.

These and other promising uses of AI are covered in the first feature of this handbook. The explosion in electronic health records, for one, is building the quantity and quality of data that AI needs to find correlations in demographic information and estimate a patient's risk of health disorders. But patient trust and insufficient data integration are obstacles to broader AI adoption.

Next, we examine how the role of AI in healthcare in clinical applications is mostly limited to radiology, while nonclinical uses are more varied, such as medication development at pharmaceutical companies and chatbots that help automate provider back offices and disease-management platforms.

Finally, we report on a recent Optum survey that shows strong growth in AI adoption in healthcare, especially to automate manual processes, resulting in worker redeployments internally. Yet the vast majority of survey respondents said hiring people with AI skills is a priority and retraining current employees for this brave new world is not happening fast enough.

By

• David Essex, Industry Editor