Competitive exception learning using fuzzy frequency distributions

A competitive exception learning algorithm for finding a non-linear mapping is proposed which puts the emphasis on the discovery of the important exceptions rather than the main rules. To do so,we first cluster the output space using a competitive fuzzy clustering algorithm and derive a fuzzy frequency distribution describing the general, average system's output behavior. Next, we look for a fuzzy partitioning of the input space in such away that the corresponding fuzzy output frequency distributions `deviate at most' from the average one as found in the first step. In this way, the most important `exceptional regions' in the input-output relation are determined. Using the joint input-output fuzzy frequency distributions, the complete input-output function as extracted from the data, can be expressed mathematically. In addition, the exceptions encountered can be collected and described as a set of fuzzy if-then-else-rules. Besides presenting a theoretical description of the new exception learning algorithm, we report on the outcomes of certain practical simulations.competitive learning;exception learning;fuzzy pattern recognition

Financial Markets Analysis by Probabilistic Fuzzy Modelling

For successful trading in financial markets, it is important to develop financial models where one can identify different states of the market for modifying one???s actions. In this paper, we propose to use probabilistic fuzzy systems for this purpose. We concentrate on Takagi???Sugeno (TS) probabilistic fuzzy systems that combine interpretability of fuzzy systems with the statistical properties of probabilistic systems. We start by recapitulating the general architecture of TS probabilistic fuzzy rule-based systems and summarize the corresponding reasoning schemes. We mention how probabilities can be estimated from a given data set and how a probability distribution can be approximated by a fuzzy histogram. We apply our methodology for financial time series analysis and demonstrate how a probabilistic TS fuzzy system can be identified, assuming that a linguistic term set is given. We illustrate the interpretability of such a system by inspecting the rule bases of our models.time series analysis;data-driven design;fuzzy reasoning;fuzzy rule base;probabilistic fuzzy systems

Relative Distress and Return Distribution Characteristics of Japanese Stocks, a Fuzzy-Probabilistic Approach

In this article, we demonstrate that a direct relation exists between the context of Japanese firms indicating relative distress and conditional return distribution properties. We map cross-sectional vectors with company characteristics on vectors with return feature vectors, using a fuzzy identification technique called Competitive Exception Learning Algorithm (CELA)1. In this study we use company characteristics that follow from capital structure theory and we relate the recognized conditional return properties to this theory. Using the rules identified by this mapping procedure this approachenables us to make conditional predictions regarding the probability of a stock's or a group of stocks' return series for different return distribution classes (actually return indices). Using these findings, one may construct conditional indices that may serve as benchmarks. These would be particularly useful for tracking and portfolio management.capital structure;asset pricing;fuzzy systems;conditional return distribution;heuristic learning

Magnesium sulfate in aneurysmal subarachnoid hemorrhage: a randomized controlled trial

BACKGROUND AND PURPOSE: Magnesium reverses cerebral vasospasm and reduces infarct volume after experimental subarachnoid hemorrhage (SAH) in rats. We aimed to assess whether magnesium reduces the frequency of delayed cerebral ischemia (DCI) in patients with aneurysmal SAH. METHODS: Patients were randomized within 4 days after SAH. Magnesium sulfate therapy consisted of a continuous intravenous dose of 64 mmol/L per day, to be started within 4 days after SAH and continued until 14 days after occlusion of the aneurysm. The primary outcome DCI (defined as the occurrence of a new hypodense lesion on computed tomography compatible with clinical features of DCI) was analyzed according to the "on-treatment" principle. For the secondary outcome measures "poor outcome" (Rankin >3) and "excellent outcome" (Rankin 0), we used the "intention-to-treat" principle. RESULTS: A total of 283 patients were randomized. Magnesium treatment reduced the risk of DCI by 34% (hazard ratio, 0.66; 95% CI, 0.38 to 1.14). After 3 months, the risk reduction for poor outcome was 23% (risk ratio, 0.77; 95% CI, 0.54 to 1.09). At that time, 18 patients in the treatment group and 6 in the placebo group had an excellent outcome (risk ratio, 3.4; 95% CI, 1.3 to 8.9). CONCLUSIONS: This study suggests that magnesium reduces DCI and subsequent poor outcome, but the results are not yet definitive. A next step should be a phase III trial to confirm the beneficial effect of magnesium therapy, with poor outcome as primary outcom

The Inter-rater Variability of Clinical Assessment in Post-anoxic Myoclonus.

Acute post-anoxic myoclonus (PAM) can be divided into an unfavorable (generalized/subcortical) and more favorable ((multi)focal/cortical) outcome group that could support prognostication in post-anoxic encephalopathy; however, the inter-rater variability of clinically assessing these PAM subtypes is unknown. We prospectively examined PAM patients using a standardized video protocol. Videos were rated by three neurologists who classified PAM phenotype (generalized/(multi)focal), stimulus sensitivity, localization (proximal/distal/both), and severity (Clinical Global Impression-Severity Scale (CGI-S) and Unified Myoclonus Rating Scale (UMRS)). Poor inter-rater agreement was found for phenotype and stimulus sensitivity (κ=-0.05), moderate agreement for localization (κ=0.46). Substantial agreement was obtained for the CGI-S (intraclass correlation coefficient (ICC)=0.64) and almost perfect agreement for the UMRS (ICC=0.82). Clinical assessment of PAM is not reproducible between physicians, and should therefore not be used for prognostication. PAM severity measured by the UMRS appears to be reliable; however, the relation between PAM severity and outcome is unknown

Long-Term Outcome of Patients With a Hematologic Malignancy and Multiple Organ Failure Admitted at the Intensive Care

Objectives: Historically, patients with a hematologic malignancy have one of the highest mortality rates among cancer patients admitted to the ICU. Therefore, physicians are often reluctant to admit these patients to the ICU. The aim of our study was to examine the survival of patients who have a hematologic malignancy and multiple organ failure admitted to the ICU. Design: This retrospective cohort study, part of the HEMA-ICU study group, was designed to study the survival of patients with a hematologic malignancy and organ failure after admission to the ICU. Patients were followed for at least 1 year. Setting: Five university hospitals in the Netherlands. Patients: One-thousand ninety-seven patients with a hematologic malignancy who were admitted at the ICU. Interventions: None. Measurements and Main Results: Primary outcome was 1-year survival. Organ failure was categorized as acute kidney injury, respiratory failure, hepatic failure, and hemodynamic failure; multiple organ failure was defined as failure of two or more organs. The World Health Organization performance score measured 3 months after discharge from the ICU was used as a measure of functional outcome. The 1-year survival rate among these patients was 38%. Multiple organ failure was inversely associated with long-term survival, and an absence of respiratory failure was the strongest predictor of 1-year survival. The survival rate among patients with 2, 3, and 4 failing organs was 27%, 22%, and 8%, respectively. Among all surviving patients for which World Health Organization scores were available, 39% had a World Health Organization performance score of 0–1 3 months after ICU discharge. Functional outcome was not associated with the number of failing organs. Conclusions: Our results suggest that multiple organ failure should not be used as a criterion for excluding a patient with a hematologic malignancy from admission to the ICU

Myoclonus in comatose patients with electrographic status epilepticus after cardiac arrest: corresponding EEG patterns, effects of treatment and outcomes

Objective: To clarify the significance of any form of myoclonus in comatose patients after cardiac arrest with rhythmic and periodic EEG patterns (RPPs) by analyzing associations between myoclonus and EEG pattern, response to anti-seizure medication and neurological outcome.Design: Post hoc analysis of the prospective randomized Treatment of ELectroencephalographic STatus Epilepticus After Cardiopulmonary Resus-citation (TELSTAR) trial.Setting: Eleven ICUs in the Netherlands and Belgium.Patients: One hundred and fifty-seven adult comatose post-cardiac arrest patients with RPPs on continuous EEG monitoring. Interventions: Anti-seizure medication vs no anti-seizure medication in addition to standard care.Measurements and Main Results: Of 157 patients, 98 (63%) had myoclonus at inclusion. Myoclonus was not associated with one specific RPP type. However, myoclonus was associated with a smaller probability of a continuous EEG background pattern (48% in patients with vs 75% without myoclonus, odds ratio (OR) 0.31; 95% confidence interval (CI) 0.16-0.64) and earlier onset of RPPs (24% vs 9% within 24 hours after cardiac arrest, OR 3.86;95% CI 1.64-9.11). Myoclonus was associated with poor outcome at three months, but not invariably so (poor neurological outcome in 96% vs 82%, p = 0.004). Anti-seizure medication did not improve outcome, regardless of myoclonus presence (6% good outcome in the intervention group vs 2% in the control group, OR 0.33; 95% CI 0.03-3.32).Conclusions: Myoclonus in comatose patients after cardiac arrest with RPPs is associated with poor outcome and discontinuous or suppressed EEG. However, presence of myoclonus does not interact with the effects of anti-seizure medication and cannot predict a poor outcome without false positives.Neurological Motor Disorder

Clinically relevant potential drug-drug interactions in intensive care patients: a large retrospective observational multicenter study

Purpose: Potential drug-drug interactions (pDDIs) may harm patients admitted to the Intensive Care Unit (ICU). Due to the patient's critical condition and continuous monitoring on the ICU, not all pDDIs are clinically relevant. Clinical decision support systems (CDSSs) warning for irrelevant pDDIs could result in alert fatigue and overlooking important signals. Therefore, our aim was to describe the frequency of clinically relevant pDDIs (crpDDIs) to enable tailoring of CDSSs to the ICU setting. Materials & methods: In this multicenter retrospective observational study, we used medication administration data to identify pDDIs in ICU admissions from 13 ICUs. Clinical relevance was based on a Delphi study in which intensivists and hospital pharmacists assessed the clinical relevance of pDDIs for the ICU setting. Results: The mean number of pDDIs per 1000 medication administrations was 70.1, dropping to 31.0 when con -sidering only crpDDIs. Of 103,871 ICU patients, 38% was exposed to a crpDDI. The most frequently occurring crpDDIs involve QT-prolonging agents, digoxin, or NSAIDs. Conclusions: Considering clinical relevance of pDDIs in the ICU setting is important, as only half of the detected pDDIs were crpDDIs. Therefore, tailoring CDSSs to the ICU may reduce alert fatigue and improve medication safety in ICU patients. ? 2020 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).Perioperative Medicine: Efficacy, Safety and Outcome (Anesthesiology/Intensive Care

Magnesium in subarachnoid hemorrhage

The main objective of this thesis was to determine the role of serum magnesium in the pathophysiology after subarachnoid hemorrhage (SAH) and to assess the effect of magnesium treatment in reducing cerebral ischemia in experimental SAH and in improving clinical outcome in patients with aneurysmal SAH. In Chapter 2 we reviewed the potentials of magnesium treatment in subarachnoid hemorrhage by describing the pathophysiology of ischemia after SAH and the many ways magnesium may interfere with this. In Chapter 3 we described a study in which cortical spreading depressions (CSDs) are induced by topical administration of potassium chloride in rat brain. We demonstrated that intravenous magnesium administration reduced CSDs and delayed anoxic depolarization in intact rat brain. Therefore we hypothesized that the neuroprotective role of magnesium in cerebral ischemia is partly due to effective suppression of ischemia-induced depolarization. In Chapter 4 we induced an experimental subarachnoid hemorrhage in the rat by means of the endovascular filament model. MRI measurements were performed on a 4.7T NMR spectrometer 1 and 48 hours after SAH and 9 days thereafter. We showed that it is feasible to detect alterations of in-vivo vessel diameter and blood flow velocities and their consequences for brain damage after experimental SAH in the rat. The increase of the infarct and the concomitant vasoconstriction suggest that delayed cerebral ischemia after SAH occurs in rats and that vasoconstriction may play an important role. In the study described in Chapter 5 we also used the endovascular filament method to induce SAH in the rat. Extracellular direct current potentials were continuously recorded from 6 Ag/AgCl electrodes, before and up to 90 minutes following SAH. Next, animals were transferred to the 4.7T NMR spectrometer. We demonstrated that prolonged depolarizations occur immediately after SAH and that the duration of these depolarizations is related to the extent of ischemic lesions observed on MRI. Moreover, we found that pretreatment with magnesium sulfate reduces the duration of the depolarizations and the extent of the ischemic lesions. Cortical spreading depressions play a minor role, if any, in the acute pathophysiology of SAH. In Chapter 6 a clinical study is described in which we measured serum magnesium in 107 consecutive patients admitted within 48 hours after SAH. Hypomagnesemia is frequently present after SAH (38%) and is associated with the amount of subarachnoid blood (cisternal blood p=0.006; ventricular blood p=0.005), a longer duration of unconsciousness (p=0.007), and a worse clinical condition at admission (p=0.001). Hypomagnesemia occurring between days 2 and 12 after SAH predicts DCI (HR 3.2; 95% CI 1.1-8.9). In Chapter 7 we describe the relation between hypomagnesemia and ECG abnormalities after SAH. Lower serum magnesium levels were related to less pronounced increase in the QTc interval and a long PR interval. Although the direction of the relation was unexpected, decreased serum magnesium might be the missing link between SAH and ECG abnormalities. In Chapter 8 we describe the results of our dose-finding study, preceding our randomized controlled trial. We found that with a continuous intravenous dosage of 64 mmol per day, serum magnesium levels after SAH maintained within the pursued range of 1.0-2.0 mmol/l for 14 days. In Chapter 9 we confirmed that with the dosage schedule found in Chapter 7 serum magnesium levels of 1.0-2.0 mmol/l can easily be maintained without severe side effects in a vast majority of patients. In Chapter 10 we describe the results of our randomized controlled trial performed with the above mentioned dosage regime in 283 patients. Magnesium treatment reduced the risk of DCI by 34% (HR 0.66; 95% CI 0.38-1.14). The risk reduction for poor outcome after 3 months was 23% (RR 0.77; 95% CI 0.54-1.09). At that time 18 patients in the treatment group and 6 in the placebo group had an excellent outcome (RR for non-excellent outcome 0.91; 95% CI 0.84-0.98). This study shows that there is a strong tendency towards a reduction of DCI and subsequent poor outcome in patients treated with magnesium, but as yet, the evidence for the introduction of magnesium treatment in clinical practice is inconclusive. A large phase III trial with functional recovery as the primary measure of outcome should provide final evidence for the effect of magnesium therapy in addition to the standard therapy

Financial markets analysis by using a probabilistic fuzzy modelling approach

For successful trading in financial markets, it is important to develop financial models where one can identify different states of the market for modifying one’s actions. In this paper, we propose to use probabilistic fuzzy systems for this purpose. We concentrate on Takagi–Sugeno (TS) probabilistic fuzzy systems that combine interpretability of fuzzy systems with the statistical properties of probabilistic systems. We start by recapitulating the general architecture of TS probabilistic fuzzy rule-based systems and summarize the corresponding reasoning schemes. We mention how probabilities can be estimated from a given data set and how a probability distribution can be approximated using a fuzzy histogram technique. We apply our methodology to financial time series analysis and demonstrate how a probabilistic TS fuzzy system can be identified, assuming that a linguistic term set is given. We illustrate the interpretability of such a system by inspecting the rule bases of our induced models