The conversational agent was able to effectively interact with users via telephone and compile relevant pre-procedure information. The ability to understand conversational user queries and respond appropriately improved significantly with larger amounts of training data. Optimal performance was seen with a classification threshold of 0.3 and a combined rule-based/machine learning technique. Conclusions: Various pre-procedure issues create substantial risk of procedure cancellation or patient harm, such as eating prior to a procedure or an unidentified contrast allergy. Although screening for these issues is generally performed by human experts, weaknesses of this approach include labor costs, lack of standardization, and the potential for human error. We present an automated machine learning approach that offers an inexpensive, systematic tool for pre-procedure planning. We believe optimal results will be seen in a strategy that combines both human evaluation and assessment by a standardized machine learning agent.

Percutaneous renal ablation is a nephron-sparing approach for selected patients with renal cell carcinoma. Common complications include hemorrhage, injury to the urinary collecting system, and abscess formation. The purpose of this article is to present a case of vascular air embolism as a complication of pneumodissection performed during percutaneous ablation of renal cell carcinoma, discuss its successful percutaneous management, review common complications of renal ablation, and outline steps physicians can take to lessen these complications.