CompAS: A new approach to commonality and variability analysis with applications in computer assisted orthopaedic surgery

In rapidly evolving domains such as Computer Assisted Orthopaedic Surgery (CAOS) emphasis is often put first on innovation and new functionality, rather than in developing the common infrastructure needed to support integration and reuse of these innovations. In fact, developing such an infrastructure is often considered to be a high-risk venture given the volatility of such a domain. We present CompAS, a method that exploits the very evolution of innovations in the domain to carry out the necessary quantitative and qualitative commonality and variability analysis, especially in the case of scarce system documentation. We show how our technique applies to the CAOS domain by using conference proceedings as a key source of information about the evolution of features in CAOS systems over a period of several years. We detect and classify evolution patterns to determine functional commonality and variability. We also identify non-functional requirements to help capture domain variability. We have validated our approach by evaluating the degree to which representative test systems can be covered by the common and variable features produced by our analysis.

Advantages and pitfalls in computer assisted orthopedic surgery planning using rapid-prototyped guides

Durch die von Rapid Prototyping gebotenen Möglichkeiten können computergestützte 3D Operationsplanungen präzise in der Operation umgesetzt werden. An der Universitätsklinik Balgrist wurden in den letzten 3 Jahren nahezu 100 Patienten erfolgreich behandelt, deren Operation in 3D geplant und mit patienten-spezifischen Schablonen umgesetzt wurde. Wir beschreiben die Genauigkeit dieser Methode und berichten über die hierbei gesammelten Erfahrungen. Aufgrund der Flexibilität der Rapid Prototyping Technologie, gibt es nicht immer nur einen Weg wie eine 3D geplante Operation umgesetzt werden kann. Wir zeigen daher anhand von Fallbeispielen unterschiedliche Strategien auf und beschreiben deren Vor- und Nachteile. Ausserdem präsentieren wir die Weiterentwicklung der Methode zur Anwendung an kleinerer Anatomie wie Knochen des Handgelenkes oder der Finger.

Randomized comparisons among health informatics students identify hypertutorial features as improving web-based instruction.

Hypertutorials optimize five features - presentation, learner control, practice, feedback, and elaborative learning resources. Previous research showed graduate students significantly and overwhelmingly preferred Web-based hypertutorials to conventional "Book-on-the-Web" statistics or research design lessons. The current report shows that the source of hypertutorials' superiority in student evaluations of instruction lies in their hypertutorial features. Randomized comparisons between the two methodologies were conducted in two successive iterations of a graduate level health informatics research design and evaluation course. The two versions contained the same text and graphics, but differed in the presence or absence of hypertutorial features: Elaborative learning resources, practice, feedback, and amount of learner control. Students gave high evaluations to both Web-based methodologies, but consistently rated the hypertutorial lessons as superior. Significant differences localized in the hypertutorial subscale that measured student responses to hypertutorial features.