PubMed · 4797342
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H Yamamura. 1973. [Anesthesia and CO2].. https://pubmed.ncbi.nlm.nih.gov/4797342/
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The medicolegal approach to cases of anaesthetic-associated mortality and anaesthetic contributory death (ACD) occurring in Johannesburg, South Africa is presented. The approach adopted has been found to be reasonably workable in practice and places heavy emphasis on the surgical and anaesthetic-related reasons for perioperative deaths and, in particular, on their multifactorial aetiology. It is recognised that in view of the multifactorial nature of the anaesthetic environment certain errors in clinical anaesthetic management are neither precisely quantifiable nor assessable. It is further emphasized that perioperative quality control programs as well as Inquest Court proceedings should comprise input by a team of specialists and which include clinical anaesthesiologists, surgeons and forensic pathologists.
We present an analysis of the computational features of neural networks and fuzzy logic architectures which attempts to explain their recent popularity as well as their drawbacks. Based upon many reports in several fields, we identify the key computational requirements in the clinical laboratory setting, and review several classical tools. In particular we make the observation that all of these needs may be viewed as a search for an appropriate mathematical mapping. We suggest that the neural networks promise as a universal function approximant is the main source of its apparent attractivity. We then describe a customized neural network architecture as a non-linear, adaptive signal processor for integrated monitoring. This architecture is employed in the Adaptive Real-Time Anesthesiologist Associate (ARTAA) system, which has been developed as a joint project at the Department of Anesthesiology, Albert Einstein Medical Center and the Electrical and Computer Engineering Department, Drexel University in Philadelphia, USA. In this application the neural network realizes a non-linear scalar map from the set of physiological signals to a vital function status (VFS) indicator. The system is now under clinical testing.
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