Year: 2016
Type: book-chapter
Abstract: This chapter introduces the problem of the automatic supervision of laser-induced effects during laser surgery. A top-down approach is used to tackle this problem: specific circumstances in which surgeons would value enhanced information regarding the effects of their laser actions on tissues are identified. The problem is grounded in the identification of variables of interest that are selected as target for the supervision. In the scope of this thesis, we explore the application of artificial cognitive approaches to monitor these variables in a surgical scenario. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Source: Springer theses
Author: Loris Fichera
Institutions: Italian Institute of Technology, University of Genoa
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W2506797860