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• W2917807767 abstract "Data suggests that physicians performing procedures have a limited understanding of equipment cost [1, 2]. Since material cost and other economic issues are not a focus of traditional medical training, some interventional radiologists may be unable to perform effective cost analysis to select equipment in an economically optimized way. We use machine learning to develop a tool allowing IR physicians to rapidly assess equipment cost while performing a procedure. Our cost assessment tool was developed for the Google Home smart speaker device. Natural language processing was implemented using the Dialogflow application programming interface (API). A Python script deployed on a cloud server was used to query an equipment cost database and return an appropriate result. We performed an extensive literature review to compile cost data for over 1500 types of IR equipment, including wires, catheters, sheaths, stents, embolization materials, and various other devices. The smart speaker tool was able to successfully understand human language and effectively provide cost data in response to a verbal query within 2 seconds of a request. Optimal performance was seen with a classification threshold of 0.3 using the hybrid (rule-based and machine learning) Dialogflow technique. System performance improved with increasing amounts of training data. The available literature suggests that current medical training does not adequately address economic issues such as equipment cost. Smart speakers offer a powerful solution to this problem in IR, as they allow procedural physicians in surgical scrub to attain rapid information by simply “asking the room” to receive a response. Advantages of this approach include the elegance of a conversational interface, sterility, and the ability to rapidly access specialized information not immediately available in a traditional web search. This tool may allow interventional radiologists to better understand equipment cost and encourage economically responsible device selection." @default.
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• W2917807767 date "2019-03-01" @default.
• W2917807767 modified "2023-09-25" @default.
• W2917807767 title "03:27 PM Abstract No. 144 A natural language processing tool for real-time cost assessment in interventional radiology" @default.
• W2917807767 doi "https://doi.org/10.1016/j.jvir.2018.12.194" @default.
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