Recent studies show that artificial intelligence algorithms can help radiologists improve the speed and accuracy of interpreting X-rays, CT scans, and other types of diagnostic images. Putting the technology into everyday clinical use, however, is challenging because of the complexities of development, testing, and obtaining regulatory approval. But a concept adapted from the world of PCs and smartphones – the app store – shows promise as a tool for bringing radiology AI from trials into day-to-day practice.
What AI “App Stores” Will Mean for Radiology
Recent studies show that artificial intelligence algorithms can help radiologists improve the speed and accuracy of interpreting X-rays, CT scans, and other types of diagnostic images. Putting the technology into everyday clinical use, however, is challenging because of the complexities of development, testing, and obtaining regulatory approval. But a concept adapted from the world of PCs and smartphones – the app store – shows promise as a tool for bringing radiology AI from trials into day-to-day practice. By taking over routine tasks, adding quality checks, and enhancing diagnostic accuracy, AI algorithms can be expected to improve clinical outcomes. Already, radiology algorithms have proven equal to, and in some cases better than, an average radiologist at identifying breast cancer on screening mammograms. The recent emergence of AI marketplaces is accelerating the adoption of AI algorithms, helping to manage growing workloads while providing doctors with tools to improve diagnoses, treatments, and, ultimately, patient outcomes.