Shadow Learning: Building Robotic Surgical Skill When Approved Means Fail

Reactive Mobility by Failure: When Fail Means Move

Mobile agent development is mainly supported by Java-based platforms and tools. However, the weak mobility model they use, the lack of adequate support for developing inference and reasoning mechanisms, added to the inherent complexity of building location-aware software, impose strong limitations for developing mobile intelligent agent systems. In this article we present MoviLog, a platform fo...

Modeling Surgical Skill Learning with Cognitive Simulation

We used a cognitive architecture (ACT-R) to explore the procedural learning of surgical tasks and then to understand the process of perceptual motor learning and skill decay in surgical skill performance. The ACT-R cognitive model simulates declarative memory processes during motor learning. In this ongoing study, four surgical tasks (bimanual carrying, peg transfer, needle passing, and suture ...

Machine Learning Approach for Skill Evaluation in Robotic-Assisted Surgery

Evaluating surgeon skill has predominantly been a subjective task. Development of objective methods for surgical skill assessment are of increased interest. Recently, with technological advances such as robotic-assisted minimally invasive surgery (RMIS), new opportunities for objective and automated assessment frameworks have arisen. In this paper, we applied machine learning methods to automat...

When Intuitions Fail

The title of this article looks in two different directions. It asks, "When do intuitions fail?" hoping to locate the conditions under which intuitions are likely to beunreliable.But it can also be the subordinate clause, of the question, "When intuitions fail, what can we do?": Both approaches, the remedial and the prophylactic, will be considered here. In 1951, Carl Voegelin and Zellig Harris...

When the Eyes Fail