Artificial Intelligence In Radiology Practice: The "Augmented Radiologist"

Abstract

Artificial intelligence (AI), which can "see" more than human radiologists in areas like tumor size, shape, morphology, texture, and kinetics, is highly anticipated in the medical field, especially in radiology. This will allow for better care through earlier detection or more accurate reports. AI is also capable of managing sizable data sets in high-dimensional environments. But it's important to remember that AI is only as good as the training data it has access to, which should ideally be enough to cover every variation. However, content knowledge and the capacity for near-optimal solution finding are the primary characteristics of human intelligence. Reviewing the complexity of radiology workplaces today and outlining their benefits and drawbacks is the aim of this paper. We also provide an overview of the various AI types and features that have been utilized thus far. We also discuss how AI and human intelligence differ in their ability to solve problems. We introduce "explainable AI," a new kind of AI that should allow for a balance or collaboration between AI and human intelligence, bringing both domains into compliance with legal requirements. We suggest developing an artificial intelligence (AI) assistant to assist (pediatric) radiologists, freeing up their brains for general tasks.

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