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        Comparison of Urologist Satisfaction for Different Types of Prostate MRI Reports: A Large Sample Investigation

        Zhong Jinman,Qin Weijun,Li Yu,Wang Yang,Huan Yi,Ren Jing 대한영상의학회 2020 Korean Journal of Radiology Vol.21 No.12

        Objective: To evaluate urologist satisfaction on structured prostate MRI reports, including report with tumor-node-metastasis (TNM) staging (report B) and with Prostate Imaging Reporting and Data System (PI-RADS) score with/without TNM staging (report C, report with PI-RADS score only [report C-a] and report with PI-RADS score and TNM staging [C-b]) compared with conventional free-text report (report A). Materials and Methods: This was a prospective comparative study. Altogether, 3015 prostate MRI reports including reports A, B, C-a, and C-b were rated by 13 urologists using a 5-point Likert Scale. A questionnaire was used to assess urologist satisfaction based on the following parameters: correctness, practicality, and urologist subjectivity. Kruskal-Wallis H-test followed by Nemenyi test was used to compare urologists’ satisfaction parameters for each report type. The rate of urologist-radiologist recalls for each report type was calculated. Results: Reports B and C including its subtypes had higher ratings of satisfaction than report A for overall satisfaction degree, and parameters of correctness, practicality, and subjectivity (p < 0.05). There was a significant difference between report B and C (p < 0.05) in practicality score, but no statistical difference was found in overall satisfaction degree, and correctness and subjectivity scores (p > 0.05). Compared with report C-b (p > 0.05), report B and C-a (p < 0.05) showed a significant difference in overall satisfaction degree and parameters of practicality and subjectivity. In terms of correctness score, neither report C-a nor C-b had a significant difference with report B (p > 0.05). No statistical difference was found between report C-a and C-b in overall satisfaction degree and all three parameters (p > 0.05). The rate of urologist-radiologist recalls for reports A, B, C-a and C-b were 29.1%, 10.8%, 18.1% and 11.2%, respectively. Conclusion: Structured reports, either using TNM or PI-RADS are highly preferred over conventional free-text reports and lead to fewer report-related post-hoc inquiries from urologists.

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        New methodologies for predicting corridor travel time mean and reliability

        Zifeng Wu,Laurence R. Rilett,Weijun Ren 서울시립대학교 도시과학연구원 2022 도시과학국제저널 Vol.26 No.3

        Accurate travel time prediction is very important for real-time traveller information systems. Many existing traveller information systems provide point estimates of forecast travel times. Often the forecast corridor travel time is estimated as a direct summation of the forecast link travel times on the route. This approach neglects the correlation between link travel times and may lead to inaccurate route travel time forecasts. This paper improves upon the simple addition method by accounting for the dependency of link travel times on the arrival time at that specific link which further correlates to its preceding links. In addition, this paper also explores the potential of using the nonlinear autoregressive with exogenous inputs (NARX) model and feedforward neural network model to forecast the corridor travel time mean and reliability metrics. To the authors knowledge this is the first time, short-term travel time reliability is measured by a reliability interval which is based on the forecasts of corridor travel time mean and standard deviation. The prediction methodologies developed in this paper are tested on an urban arterial that has been instrumented with Bluetooth readers so empirical travel times are available. It was found that the proposed NARX model outperforms the other models that were studied with respect to mean corridor travel time prediction. In terms of the reliability interval prediction, the performance of various models is presented as a Pareto Optimal Frontier trading off accuracy and usability. The proposed NARX model and three other tested models are all on the Pareto Optimal Frontier.

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