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Student Modeling in Orthopedic Surgery Training: Exploiting Symbiosis between Temporal Bayesian Networks and Fine-grained Didactic Analysis

Cognitive approaches have been used for student modeling in intelligent tutoring systems (ITSs). Many of those systems have tackled fundamental subjects such as mathematics, physics, and computer programming. The change of the students cognitive behavior over time, however, has not been considered and modeled systematically. Furthermore, the nature of domain knowledge in specific subjects such as orthopedic surgery, in which pragmatic knowledge could play an important role, has also not been taken into account deliberately. We believe that the temporal dimension in modeling the students knowledge state and cognitive behavior is critical, especially in such domains. In this paper, we propose an approach for student modeling and diagnosis, which is based on a symbiosis between temporal Bayesian networks and fine-grained didactic analysis. The latter may help building a powerful domain knowledge model and the former may help modeling the learners complex cognitive behavior, so as to be able to provide him or her with relevant feedback during a problem-solving process. To illustrate the application of the approach, we designed and developed several key components of an intelligent learning environment for teaching the concept of sacro-iliac screw fixation in orthopedic surgery, for which we videotaped and analyzed six surgical interventions in a French hospital. A preliminary gold-standard validation suggests that our diagnosis component is able to produce coherent diagnosis with acceptable response time.

BiopSym: a simulator for enhanced learning of ultrasound-guided prostate biopsy.

This paper describes a simulator of ultrasound-guided prostate biopsies for cancer diagnosis. When performing biopsy series, the clinician has to move the ultrasound probe and to mentally integrate the real-time bi-dimensional images into a three-dimensional (3D) representation of the anatomical environment. Such a 3D representation is necessary to sample regularly the prostate in order to maximize the probability of detecting a cancer if any. To make the training of young physicians easier and faster we developed a simulator that combines images computed from three-dimensional ultrasound recorded data to haptic feedback. The paper presents the first version of this simulator.

A virtual reality simulator combining a learning environment and clinical case database for image-guided prostate biopsy

The recent availability of navigation systems for mapping and targeting of transrectal ultrasound (TRUSS) guided prostate biopsies revealed new opportunities in training the clinician. This paper describes a simulator for TRUSS guided prostate biopsy that offers similar information, enhanced by a complete learning environment. Various exercises have been developed in accordance with a didactical study identifying the training needs. A dedicated clinical case database fed by a prostate navigation system provides a large patient prostate image database that covers the main situations encountered during clinical practice. A haptic device is used to enable complete biopsy procedures or practice specific tasks. This paper also presents work in progress of the evaluation of such a simulator.

Initial Validation of a Virtual-Reality Learning Environment for Prostate Biopsies: Realism Matters!

BACKGROUND AND PURPOSE A virtual-reality learning environment dedicated to prostate biopsies was designed to overcome the limitations of current classical teaching methods. The aim of this study was to validate reliability, face, content, and construct of the simulator. MATERIALS AND METHODS The simulator is composed of (a) a laptop computer, (b) a haptic device with a stylus that mimics the ultrasound probe, (c) a clinical case database including three-dimensional (3D) ultrasound volumes and patient data, and (d) a learning environment with a set of progressive exercises including a randomized 12-core biopsy procedure. Both visual (3D biopsy mapping) and numerical (score) feedback are given to the user. The simulator evaluation was conducted in an academic urology department on 7 experts and 14 novices who each performed a virtual biopsy procedure and completed a face and content validity questionnaire. RESULTS The overall realism of the biopsy procedure was rated at a median of 9/10 by nonexperts (7.1-9.8). Experts rated the usefulness of the simulator for the initial training of urologists at 8.2/10 (7.9-8.3), but reported the range of motion and force feedback as significantly less realistic than novices (P=0.01 and 0.03, respectively). Pearson r correlation coefficient between correctly placed biopsies on the right and left side of the prostate for each user was 0.79 (P<0.001). The 7 experts had a median score of 64% (59%-73%), and the 14 novices a median score of 52% (43%-67%), without reaching statistical significance (P=0.19). CONCLUSION The newly designed virtual-reality learning environment proved its versatility and its reliability, face, and content were validated. Demonstrating the construct validity will necessitate improvements to the realism and scoring system used.Abstract Background and Purpose: A virtual-reality learning environment dedicated to prostate biopsies was designed to overcome the limitations of current classical teaching methods. The aim of this study was to validate reliability, face, content, and construct of the simulator. Materials and Methods: The simulator is composed of (a) a laptop computer, (b) a haptic device with a stylus that mimics the ultrasound probe, (c) a clinical case database including three-dimensional (3D) ultrasound volumes and patient data, and (d) a learning environment with a set of progressive exercises including a randomized 12-core biopsy procedure. Both visual (3D biopsy mapping) and numerical (score) feedback are given to the user. The simulator evaluation was conducted in an academic urology department on 7 experts and 14 novices who each performed a virtual biopsy procedure and completed a face and content validity questionnaire. Results: The overall realism of the biopsy procedure was rated at a median of 9/10 by nonex...

Novel Technology for Learning in Medicine

In this chapter we will present some medical educational approaches together with their links to different learning objectives and learning situations. We will also present various forms of computer-based technology, which aim to enhance the teaching and learning capabilities of doctors, mostly in the form of 3D visua- lisation, simulation and haptic technology. We will focus on research conducted in the areas of spinal anaesthesia, surgery and emergency. Finally, we will emphasise some challenges of our domain which are related to the interaction between medical education, technological and computer factors.

Education tools for surgery: a simulator for pelvic surgery

This poster presents a simulator dedicated to learning a computer-aided pelvic surgery procedure. Such a technique allows to position screws in the iliac bone minimally invasively (see [1]). The objective of the simulator is to make the clinical diffusion of such new techniques integrating intra-operative data acquisition for registration easier.