Qure.ai CT scan reading technology accurately detects abnormalities

From what we can observe, digital transformation is always present in the healthcare industry, and earlier this week Qure.ai, a healthcare start-up, has launched an artificial intelligence-based system to detect abnormalities in CT scans.

This clearly demonstrates the fact that modern technologies, such as AI and machine learning, are very much present and utilised in the healthcare industry.

The technology developed by Qure.ai, when tested, turned out to be quite accurate indeed. In concrete numbers, its algorithms were pretty much on par with the findings of radiologists when examining 21,000 patient scans.

To see how this looks in practice, Qure.ai is making a dataset of 500 CT scans available for download.

The healthcare industry is facing the problem of having more images from MRIs and radiology than qualified human resources who can analyse and interpret them. The general idea is that we could use AI in order to lift some of the workload off their shoulders.

Furthermore, speed is absolutely essential when interpreting a CT scan from a stroke victim, and AI could effectively solve this problem as well. Essentially, this deals with two problems at the same time: the human resources problem and the problem of speed.

According to Qure.ai, the algorithms are 95% accurate. Over the next few years, the company is planning to continue their development by investing a further $30 million into the promising project. The results and additional details were published by Cornell University and are available to view on their site.