As well as digital technologies in general, the healthcare sector will be enhancing digital images with artificial intelligence to help pathologists to detect key signs earlier or to help with greater accuracy.
Other advantages that will arise from such technology are centered on decreasing turnaround time, prioritizing critical cases, and improving overall patient outcomes. To do so will involve innovating and developing tools for primary and secondary analysis.
These are key highlights from a new report issued by Frost & Sullivan. The report is titled “Digital Pathology: Roadmap to the Future of Medical Diagnosis.” The types of technologies within this space are digital whole slide scanning, digital imaging solutions, and offering a digital data repository, which can be subject to big data analysis.
Many of these technologies will enable researchers to access databases from the cloud and for hospitals to collaborate together, in terms of sharing images. It is also possible to send an image around the world so that a second opinion can be given from a specialist consultant.
The report charts how the regulatory landscape has shifted and there is proven method qualification to show that digital systems are very effective, resulting in the barriers to technology take-up and implementation being lower.
As an example, the digital pathology system, and artificial intelligence platform, OsteoDetect has gained approval from the U.S. Food and Drug Administration (FDA). The technology is used for the detection of distal radius fracture.
Commenting on the report, Deepak Jayakumar, Senior Research Analyst, TechVision states: “Artificial intelligence has the potential to analyze big data and find patterns and insights that could enhance patient outcomes in the field of pathology. It can serve as a supplementary or a validation tool in imaging analytics for pathologists, and help process more slides in a shorter duration.”
He goes on to assess how these technologies will appeal strongest to hospitals and diagnostic laboratories. A driver for this will be seeking cost optimization for end users. This can be realized via pay-per-use or Software-as-a-Service (SaaS) models. A side effect of this will be to disrupt traditional models within the healthcare system.
