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Fuzzy neural network (FNN), a hybrid of fuzzy logic and neural network, is computationally powerful, robust and able to model a complex nonlinear problem domain via the extraction and self-tuning of fuzzy IF-THEN rules. This yields a powerful semantic learning memory system that is useful to build intelligent decision support tools. Thermal imaging has been effectively used in the detection of infrared spectrum for the screening of potential SARS patients. This chapter proposes a cognitive approach in the study of the correlation and semantic interpretation of superficial thermal images against the true internal body temperature. Comparison between global and local semantic memories as well as Mamdani and TSK model of FNNs are presented. Existing infrared systems are commonly used at various boarder checkpoints and these have high false-negative rate. The use of FNN as a back-end of the system can significantly improves and hence serves the role of an intelligent medical decision support tool with high degree of accuracy. Extensive experimentations are conducted on real-life data taken from the Emergency Department (A&E), Tan Tock Seng Hospital (the designated SARS center in Singapore). The performance of FNN as the thermal analysis decision support system, providing plausible semantic interpretation and understanding, is highly encouraging. [ABSTRACT FROM AUTHOR]

This study aim at evaluating several cases and communication options between a surgeon-mentor and a surgeon-mentoree within a telementoring context. The simulation proved that surgical telementoring was technically feasible with a satellite link simulated at 384 Kb/s, 512 Kb/s, and 768 Kb/s and with a transmission delay of 700 ms. Results show the limitations of image communication and its acceptability for telementoring and point out an important learning process for the mentoree. This seems to indicate a more efficient learning curve than with the standard training techniques (live surgical demonstration by companionship or videoconferencing), or with the use of laparoscopic simulator and surgical robots. [ABSTRACT FROM AUTHOR]