The Implications of AI Innovation in Healthcare: The Case of the Radiology Space—Challenges and Implications

Abstract

Abstract Radiologists play an important role in the healthcare system by creating images that help to diagnose and treat various diseases and injuries. Studies show that radiologists perform 691 million exams annually, which represents 16.5% of all such procedures done worldwide while generating $23.8B in annual revenue. There is a relative shortage of radiologists with workload burnout being of increasing concern. This chapter offers an overview of the daily work-life of a hospital-based radiologist with particular emphasis on the integration and utilization of Artificial Intelligence (AI) tools in the interpretation of medical images. Radiologists often face demands of reading many subtle images in order to make accurate diagnoses of multiple patients with a quick turn-around time. Newer technologies such as MRIs have generated even more pressure to produce accurate diagnoses, and here is where AI has the potential to help radiologists. AI can help address a heightened volume of readings, identify potential abnormalities and thereby increase the percentage of accurate diagnoses more efficiently. In summary, the integration of AI into radiology can enhance diagnostic accuracy, optimize workflow efficiency and support radiologists’ delivery of high-quality patient care. AI will change and enhance radiology, but it won’t replace radiologists.

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