The X Prize Foundation announced a new $10 million contest to develop a portable device that can diagnose a wide range of diseases with the same accuracy as a panel of board-certified physicians.
The details of the contest are still being worked out, but the goal is likely to be a device that can perform a number of diagnostic tests and combine these with artificial intelligence to determine whether a subject has a particular malady. Such a device could help those who lack access to traditional medical services—and streamline access to specialty care in traditional medical treatment.
* doctor would always be involved in some way in patient diagnosis.
* This device and future devices will be a help and guide to get someone quickly to the right medical care
* The Food and Drug Administration has stated that it will not certify tech that makes a diagnosis directly
* strokes can already be diagnosed with the aid of a smart-phone application with the same degree of accuracy as with a hospital computer.
* because of FDA restrictions, the contest could lead to innovations that might only be used outside the United States
“Imagine a world where people get funneled to the right part of a complex health system at the right time,” says Eileen Bartholomew, a senior director at the X Prize Foundation. Bartholomew is working on designing the exact parameters for the prize, which will be launched in 2012. “And when consumers get into the health system, they come with data, to understand and guide their treatment.”
Bartholomew says that the contest may involve diagnosing a particular disease or could start with less ambitious challenges, such as performing a single test for a prize in the $1 million range
Smartphone diagnosis of Stroke
Recent advances in the treatment of acute ischemic stroke have made rapid acquisition, visualization, and interpretation of images a key factor for positive patient outcomes. We have developed a new teleradiology system based on a client-server architecture that enables rapid access to interactive advanced 2-D and 3-D visualization on a current generation smartphone device (Apple iPhone or iPod Touch, or an Android phone) without requiring patient image data to be stored on the device. Instead, a server loads and renders the patient images, then transmits a rendered frame to the remote device.
Results: The sensitivity, specificity, and accuracy of detecting intraparenchymal hemorrhage were 100% using the iOS device with a perfect interrater agreement (kappa = 1). The sensitivity, specificity, and accuracy of detecting acute parenchymal ischemic change were 94.1%, 100%, and 98.09% respectively for reader 1 and 97.05%, 100%, and 99.04% for reader 2 with nearly perfect interrater agreement (kappa = .8). The sensitivity, specificity, and accuracy of detecting dense vessel sign were 100%, 95.4%, and 96.19% respectively for reader 1 and 72.2%, 100%, and 95.23% for reader 2 using the iOS device with a good interrater agreement (kappa = .69). The sensitivity, specificity, and accuracy of detecting vessel occlusion on CT angiography scans were 94.4%, 100%, and 98.46% respectively for both readers using the iOS device, with perfect interrater agreement (kappa = 1). No significant difference (P less than .05) was noted in the interpretation time between the workstation and iOS device.
Conclusion: The smartphone client-server teleradiology system appears promising and may have the potential to allow urgent management decisions in acute stroke. However, this study was retrospective, involved relatively few patient studies, and only two readers. Generalizing conclusions about its clinical utility, especially in other diagnostic use cases, should not be made until additional studies are performed.