Driven by the improved accuracy and usability of CAD systems, this will result in faster and more accurate diagnoses for patients, as well as reduced pressure on doctors. By 2022, 28.4-million chronic disease scans will be fed into first-line CAD systems annually.
The Digital Health: Vendor Analysis, Emerging Technologies & Market Forecasts 2017-2022 found that AI is increasingly being applied to a varied range of use cases, from powering chatbots to understanding patients’ symptoms or interpreting genomic data sets.
It found that despite emerging use cases, the use of AI for CAD systems was still the most compelling, as it can generate significant cost savings, forecast at $126m for first-line CAD systems in 2022.
The report found that AI will be utilised in big data analytics solutions, allowing the processing of more complex datasets, such as doctors’ notes in an EHR (electronic health record). AI, EHR systems and analytics platforms will increasingly be integrated into one system.
The research also found that AI faces significant challenges. There is a widespread perceived issue with trust, largely resulting from the so-called ‘black box’. Here, AI is unable to demonstrate how it has arrived at a decision, while it is incapable to build trust as a human would (via body language for example). that AI companies should demonstrate high levels of public engagement and independent verification to ensure data is being handled in the correct way.
