Computing Reviews

Solving challenges in inter- and trans-disciplinary working teams
Korb W., Geißler N., Strauß G. Artificial Intelligence in Medicine63(3):209-219,2015.Type:Article
Date Reviewed: 09/15/15

Trans-disciplinary research requires respectable understanding and positive thinking as a team. As a researcher of the trans-disciplinary domain, I agree with the notion that a trans-disciplinary research team needs to act cooperatively toward common goals for sustainable research and development. In this aspect, it is understood that integration between medicine and engineering is becoming a more complex and complicated scenario that requires deep understanding of the background knowledge.

The human factors highlighted in this paper add merit to solving trans-disciplinary challenges and are necessary in order to tackle the challenges faced by inter- and trans-disciplinary teams. The shared mental model (SMM), cooperative learning, advocating principles, and mentoring principles are value-added approaches. The SMM allows individuals to have a sense of how a system works, interacts, and predicts, and then how systems will function in the future.

This paper will help surgeons, engineers, and psychologists to create an environment where issues regarding human factors are avoided or tackled before they get out of hand. I congratulate the authors of this paper because forming a team with an innovative cooperative working culture is a step toward improving efficiency to reach common goals.

Reviewer:  Tony Sahama Review #: CR143773 (1512-1066)

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