Combining Geometric and Probabilistic Reasoning for Computer-based Penetrating- Trauma Assessment

Design: The authors created a computer system (TraumaSCAN) that integrates three-dimensional geometric reasoning about anatomic likelihood of injury with probabilistic reasoning about injury consequences using Bayesian networks. Preliminary evaluation of TraumaSCAN was performed via a retrospective study testing performance of the system on data from 26 cases of actual gunshot wounds. Measurements: Areas under the receiver operating characteristics (ROC) curve were calculated for each condition modeled in TraumaSCAN that was present in the 26 cases. The comprehensiveness and relevance of the TraumaSCAN diagnosis for the 26 cases were used to assess the overall performance of the system. To test the ability of TraumaSCAN to handle limited findings, these measurements were calculated both with and without input of observed findings into the Bayesian network. Results: For the 11 conditions assessed, the worst area under the ROC curve with no observed findings input into the Bayesian network was 0.542 (95% CI, 0.146–0.937), the median was 0.883 (95% CI, 0.713–1.000), and the best was 1.00 (95% CI, 1.000–1.000). The worst area under the ROC curve with all observed findings input into the Bayesian network was 0.835 (95% CI, 0.602–1.000), the median was 0.941 (95% CI, 0.827–1.000), and the best was 0.992 (95% CI, 0.965–1.000). A comparison of the areas under the curve obtained with and without input of observed findings into the Bayesian network showed that there were significant differences for 2 of the 11 conditions assessed. Conclusion: A computer-based method that combines geometric and probabilistic reasoning shows promise as a tool for assessing ballistic penetrating trauma to the chest and abdomen. ■ J Am Med Inform Assoc. 2002;9:273–282. OMOLOLA I. OGUNYEMI, PHD, JOHN R. CLARKE, MD, NACHMAN ASH, MD, MSC, BONNIE L. WEBBER, PHD by gest on Jauary 5, 2016 ht://jam ia.oxfournals.org/ D ow nladed from and diagnostic reasoning in assessing a patient could serve as such a tool or knowledge aid. To be successful, computer-based assessment of penetrating trauma requires a model that 1) reflects the relationships among human anatomy, physiology and physical manifestations of injury, and 2) can take into account uncertainty about the region of damage produced by a mechanism of injury and variability in the amount of information about available patient findings. Accordingly, the research question we are investigating is as follows: Can three-dimensional geometric and probabilistic reasoning methods be successfully combined for computer-based assessment of conditions arising from ballistic penetrating trauma to the chest and abdomen? To address this issue, we have developed a prototype computer system, TraumaSCAN,3 that assesses the effects of ballistic penetrating trauma to the chest and abdomen. TraumaSCAN reasons about injured anatomic structures on the basis of information about surface wounds and bullet locations, and uses the results of this geometric reasoning process to drive diagnostic reasoning about the consequences of injury. The system is designed to take into account uncertainty about the extent of damage caused by a mechanism of injury and variability in information available about patient signs, symptoms, and test results. In this paper, we describe the methods used for penetrating trauma assessment in TraumaSCAN and present the results of retrospective testing of the system using data from 26 actual gunshot wound cases.