Identification of causal relations between haemodynamic variables, auditory evoked potentials and isoflurane by means of fuzzy logic.
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The aim of this study was to identify a possible relationship between haemodynamic variables, auditory evoked potentials (AEP) and inspired fraction of isoflurane (ISOFl). Two different models (isoflurane and mean arterial pressure) were identified using the fuzzy inductive reasoning (FIR) methodology. A fuzzy model is able to identify non-linear and linear components of a causal relationship by means of optimization of information content of available data. Nine young female patients undergoing hysterectomy under general anaesthesia were included. Mean arterial pressure (MAP), heart rate (HR), end-tidal expired carbon dioxide (CO2ET), AEP and ISOFl were monitored with a sampling time of 10 s. The AEP was extracted using an autoregressive model with exogenous input (ARX model) which decreased the processing time compared with a moving time average. The AEP was mapped into a scalar, termed the depth of anaesthesia index (DAI) normalized to 100 when the patient was awake and descending to an average of 25 during loss of consciousness. The FIR methodology identified those variables among the input variables (MAP, HR, CO2ET, DAI or ISOFl) that had the highest causal relation with the output variables (ISOFl and MAP). The variables with highest causal relation constitute the ISOFl and MAP models. The isoflurane model predicted the given anaesthetic dose with a mean error of 12.1 (SD 10.0)% and the mean arterial pressure model predicted MAP with a mean error of 8.5 (7.8)%. (+info)
Fuzzy logic and measles vaccination: designing a control strategy.
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BACKGROUND: The State of Sao Paulo, the most populous in Brazil, was virtually free of measles from 1987 until the end of 1996 when the number of cases started to rise. It reached alarming numbers in the middle of 1997 and local health authorities decided to implement a mass vaccination campaign. METHODS: Fuzzy Decision Making techniques are applied to the design of the vaccination campaign. RESULTS: The mass vaccination strategy chosen changed the natural course of the epidemic. It had a significant impact on the epidemic in the metropolitan area of Sao Paulo city, but a second epidemic in the State's interior forced the public health authorities to implement a second mass vaccination campaign 2 months after the first. CONCLUSIONS: Fuzzy Logic techniques are a powerful tool for the design of control strategies against epidemics of infectious diseases. (+info)
Which algorithm for scheduling add-on elective cases maximizes operating room utilization? Use of bin packing algorithms and fuzzy constraints in operating room management.
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BACKGROUND: The algorithm to schedule add-on elective cases that maximizes operating room (OR) suite utilization is unknown. The goal of this study was to use computer simulation to evaluate 10 scheduling algorithms described in the management sciences literature to determine their relative performance at scheduling as many hours of add-on elective cases as possible into open OR time. METHODS: From a surgical services information system for two separate surgical suites, the authors collected these data: (1) hours of open OR time available for add-on cases in each OR each day and (2) duration of each add-on case. These empirical data were used in computer simulations of case scheduling to compare algorithms appropriate for "variable-sized bin packing with bounded space." "Variable size" refers to differing amounts of open time in each "bin," or OR. The end point of the simulations was OR utilization (time an OR was used divided by the time the OR was available). RESULTS: Each day there were 0.24 +/- 0.11 and 0.28 +/- 0.23 simulated cases (mean +/- SD) scheduled to each OR in each of the two surgical suites. The algorithm that maximized OR utilization, Best Fit Descending with fuzzy constraints, achieved OR utilizations 4% larger than the algorithm with poorest performance. CONCLUSIONS: We identified the algorithm for scheduling add-on elective cases that maximizes OR utilization for surgical suites that usually have zero or one add-on elective case in each OR. The ease of implementation of the algorithm, either manually or in an OR information system, needs to be studied. (+info)
Evaluation of new online automated embolic signal detection algorithm, including comparison with panel of international experts.
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BACKGROUND AND PURPOSE: The clinical application of Doppler detection of circulating cerebral emboli will depend on a reliable automated system of embolic signal detection; such a system is not currently available. Previous studies have shown that frequency filtering increases the ratio of embolic signal to background signal intensity and that the incorporation of such an approach into an offline automated detection system markedly improved performance. In this study, we evaluated an online version of the system. In a single-center study, we compared its performance with that of a human expert on data from 2 clinical situations, carotid stenosis and the period immediately after carotid endarterectomy. Because the human expert is currently the "gold standard" for embolic signal detection, we also compared the performance of the system with an international panel of human experts in a multicenter study. METHODS: In the single-center evaluation, the performance of the software was tested against that of a human expert on 20 hours of data from 21 patients with carotid stenosis and 18 hours of data from 9 patients that was recorded after carotid endarterectomy. For the multicenter evaluation, a separate 2-hour data set, recorded from 5 patients after carotid endarterectomy, was analyzed by 6 different human experts using the same equipment and by the software. Agreement was assessed by determining the probability of agreement. RESULTS: In the 20 hours of carotid stenosis data, there were 140 embolic signals with an intensity of > or =7 dB. With the software set at a confidence threshold of 60%, a sensitivity of 85.7% and a specificity of 88.9% for detection of embolic signals were obtained. At higher confidence thresholds, a specificity >95% could be obtained, but this was at the expense of a lower sensitivity. In the 18 hours of post-carotid endarterectomy data, there were 411 embolic signals of > or =7-dB intensity. When the same confidence threshold was used, a sensitivity of 95.4% and a specificity of 97.5% were obtained. In the multicenter evaluation, a total of 127 events were recorded as embolic signals by at least 1 center. The total number of embolic signals detected by the 6 different centers was 84, 93, 108, 92, 63, and 78. The software set at a confidence threshold of 60% detected 90 events as embolic signals. The mean probability of agreement, including all human experts and the software, was 0.83, and this was higher than that for 2 human experts and lower than that for 4 human experts. The mean values for the 6 human observers were averaged to give P=0.84, which was similar to that of the software. CONCLUSIONS: By using the frequency specificity of the intensity increase occurring with embolic signals, we have developed an automated detection system with a much improved sensitivity. Its performance was equal to that of some human experts and only slightly below the mean performance of a panel of human experts (+info)
A property concept frame representation for flexible image-content retrieval in histopathology databases.
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In histopathology databases, images descriptions are collections of properties provided by experts. Image content retrieval implies comparison of such properties. The objective of this work is to enrich the traditional attribute-value representation of properties in order to take into account the polymorphism and subjectivity of properties and to manage the comparison process. In this paper we define a property concept frame (PCF) representation based on fuzzy logic to handle both representation and comparison. Seven quantifiable morphological characteristics were selected from histopathological reports to illustrate the variety of fuzzy predicates and linguistic terms in properties. The PCF representation has been tested in the context of breast pathology. It is concluded that the PCF representation provides a unification scheme to retrieve in images morphological characteristics that are described in different ways. It may enhance the relevancy of applications in various contexts such as image content-based retrieval or case-based reasoning from images. (+info)
Decision trees and fuzzy logic: a comparison of models for the selection of measles vaccination strategies in Brazil.
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In 1997, health authorities of the state of Sao Paulo, Brazil designed a vaccination campaign against measles based on a decision model that utilized fuzzy logic. The chosen mass vaccination strategy was implemented and changed the natural course of the epidemic in that state. We have built a model using a decision tree and compare it to the fuzzy logic model. Using essentially the same set of assumptions about this problem, we contrast the two approaches. The models identify the same strategy as being the best one, but exhibit differences in the ranking of the remaining strategies. (+info)
Prevention of haemodialysis-induced hypotension by biofeedback control of ultrafiltration and infusion.
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BACKGROUND: Haemodialysis-induced hypotension is still a severe complication in spite of all the progress in haemodialysis treatment. Because of its multifactorial causes, haemodialysis-induced hypotension cannot be reliably prevented by conventional ultrafiltration and sodium profiling in open-loop systems, as they are unable to adapt themselves to actual decreases in blood pressure. METHODS: A blood-pressure-guided closed-loop system, for prevention of haemodialysis-induced hypotension by biofeedback-driven computer control of both ultrafiltration and saline infusion was clinically tested in 237 treatments of seven patients prone to hypotension. As medical knowledge on multifactorial causes of hypotension is characterized by a lack in deterministic knowledge, fuzzy logic and linguistic variables were used to involve clinical experience on hypotension phenomena in terms of fuzzy knowledge. Biofeedback control is based on frequent measurements of blood pressure at 5 min intervals. Blood pressure behaviour is described by linguistic variables and fuzzy sets. Adaptive rule bases were used for the simultaneous fuzzy control of both the ultrafiltration and infusion of hypertonic saline (20% NaCl). Proper adaptation of control features to patient's conditions was provided by the critical borderline pressure, which was set by the physician individually at the beginning of each treatment. During the initial and medium phases of the sessions, ultrafiltration rates up to 150% of the average rates were applied as long as decreases in blood pressure could be compensated by saline infusion. The surplus of ultrafiltrate volume was used for blood pressure stabilization in the final phase in most instances by low ultrafiltration rates. RESULTS: The advantages of biofeedback-controlled haemodialysis were demonstrated by both decreasing the frequency of hypotonic episodes and by increasing or maintaining constant levels of systolic blood pressure during the final phase in 88% of treatments. As saline infusion was applied mainly in the initial and medium phases, blood sodium levels were not significantly higher at the end of the sessions, and interdialytic weight gain was not elevated. CONCLUSION: The application of fuzzy logic in the blood-pressure-guided biofeedback control of ultrafiltration and sodium infusion during haemodialysis is able to minimize haemodialysis-induced hypotension. (+info)
A web exercise in evidence-based medicine using cognitive theory.
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Our aim was to improve clinical reasoning skills by applying an established theory of memory, cognition, and decision making (fuzzy-trace theory) to instruction in evidence-based medicine. Decision-making tasks concerning chest pain evaluation in women were developed for medical students and internal medicine residents. The fuzzy-trace theory guided the selection of online sources (e.g., target articles) and decision-making tasks. Twelve students and 22 internal medicine residents attended didactic conferences emphasizing search, evaluation, and clinical application of relevant evidence. A 17-item Likert scale questionnaire assessed participants' evaluation of the instruction. Ratings for each of the 17 items differed significantly from chance in favor of this alternative approach to instruction. We concluded that fuzzy-trace theory may be a useful guide for developing learning exercises in evidence-based medicine. (+info)