Abstract
The role of Radiology is fundamental to the ruling in or ruling out of the disease hypothesis. Physicians order diagnostic imaging studies, technologists perform the image capture process, and radiologists analyze the images and clinical information and generate a report of their findings. The radiology report is used by the requesting physician in establishing the patient’s diagnosis and planning the path of treatment. In the radiology department each of these steps involves the use of complex integrated medical software systems to manage clinical information and images. The performance and usability of these systems is critical to the timely treatment of patients. This paper focuses on reducing radiology report turnaround times by integrating advanced algorithms and automation in the information systems responsible for managing radiology workflows.
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Stuhlman, D. (2022). A Method to Optimize and Automate the Distribution of Radiology Studies. In: Rayz, J., Raskin, V., Dick, S., Kreinovich, V. (eds) Explainable AI and Other Applications of Fuzzy Techniques. NAFIPS 2021. Lecture Notes in Networks and Systems, vol 258. Springer, Cham. https://doi.org/10.1007/978-3-030-82099-2_38
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DOI: https://doi.org/10.1007/978-3-030-82099-2_38
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