Predictive Behavior of a Computational Foot/Ankle Model through Artificial Neural Networks.

Computational models are useful tools to study the biomechanics of human joints. Their predictive performance is heavily dependent on bony anatomy and soft tissue properties. Imaging data provides anatomical requirements while approximate tissue properties are implemented from literature data, when available.

Communication training improves patient-centered provider behavior and screening for soldiers' mental health concerns.

Objective: To evaluate the effectiveness of patient-centered communication training for military providers who conduct post-deployment health screening. The half-day interactive workshop included simulated Soldier patients using video technology.

Methods: Using a quasi-experimental design, all health care providers at four military treatment facilities were recruited for data collection during a four- to nine-day site visit (23 trained providers, 28 providers in the control group, and one provider declined to participate).

Feedback mechanisms of change: How problem alerts reported by youth clients and their caregivers impact clinician-reported session content.

Objective: This study explored how clinician-reported content addressed in treatment sessions was predicted by clinician feedback group and multi-informant cumulative problem alerts that appeared in computerized feedback reports for 299 clients aged 11-18 years receiving home-based community mental health treatment.

Method: Measures included a clinician report of content addressed in sessions and additional measures of treatment progress and process (e.g.

Spleen Segmentation and Assessment in CT Images for Traumatic Abdominal Injuries.

Spleen segmentation is especially challenging as the majority of solid organs in the abdomen region have similar gray level range. Physician analysis of computed tomography (CT) images to assess abdominal trauma could be very time consuming and hence, automating this process can reduce time to treatment. The proposed method presented in this paper is a fully automated and knowledge based technique that employs anatomical information to accurately segment the spleen in CT images.

Overview of depression, post-traumatic stress disorder, and alcohol misuse among active duty service members returning from Iraq and Afghanistan, self-report and diagnosis.

Previous studies have found deployment to combat areas to be associated with an increased risk of post-traumatic stress disorder (PTSD), depression, and alcohol abuse, but many previous studies were limited by samples that were not representative of the deployed military as a whole. This study presents an overview of these three mental health problems associated with deployment among Air Force, Army, Marine Corp, and Navy service members returning from deployment to Iraq and Afghanistan between January 2007 and March 2008. With postdeployment health data on over 50,000 service men and women, including diagnostic information, we were able to estimate prevalence of those who screened positive for risk of each disorder in self-report data at two time points, as well as prevalence of diagnoses received during health care encounters within the military health care system.