SummaryArtificial intelligence is the next big thing in radiology. Artificial intelligence will change everything in radiology, from how reports are reviewed to patient care. Patient care will be at the forefront of the artificial intelligence movement. Data patterns in studies analyzed by artificial intelligence algorithms will provide preliminary reports to the radiologist. Along with preliminary reports, artificial intelligence will be able to track a patient's medical history. The future is here and has only just begun. Say no to plagiarism. Get a tailor-made essay on “Why violent video games should not be banned”?Get the original essayTags: artificial intelligence, radiologyArtificial intelligence in radiologyArtificial intelligence: is this the future of radiology? Artificial intelligence is the hottest topic in radiology in 2018. Artificial intelligence is moving from a testing phase to implementation in the medical field. Artificial intelligence ranges from algorithms trained to detect abnormalities in images to maintaining a patient's complete medical history. According to the Merriam-Webster Dictionary, artificial intelligence is: (a) a branch of computer science dealing with the simulation of intelligent behavior in computers, and (b) the ability of a machine to imitate intelligent human behavior ( 2018). Dr. Schier stated that “intelligence refers to the ability to solve problems” (2018). To understand artificial intelligence and what it means for the future, we need to understand how it works. There are many different branches and types of artificial intelligence. King and King (2018) reported the following: Machine learning is a major component of AI, which is a subfield of computer science that allows computers to learn without being explicitly programmed. This exciting technology integrates computer models and algorithms similar to the structure and function of biological neural networks in our brains. These computer models are often called “artificial neural networks.” “When these artificial neural networks process information (digital data) from many input streams, they have the ability to “learn” and modify their structure in the same way that the neurons in our brain are modified with the memory (p501). Deep learning is a large machine learning network, with data recognizing objects in images. Radiology is interested in what is in the image. Neural networks are algorithms designed to analyze thousands and thousands of images, taking the data and organizing it to reveal patterns. The combination of doctors and artificial intelligence will impact the field of radiology. Artificial intelligence software generates a preliminary report of the scan, allowing the radiologist to review the scan and add it to the report. Any critical findings will be flagged and will alarm the radiologist reading an emergent case. Artificial intelligence software will review a study and decide where on the list the review should be placed, whereas now PACS dictates the work list based on the time an analysis is ordered. “Artificial intelligence not only provides results to your preliminary reports, but can also actively analyze your report when you dictate context errors (right/left deviation)” (Sana, 2018). Artificial intelligence will provide recommended follow-ups based on protocols, making it easier.