



@article {2271,
	title = {Assessment of Disagreement: A New Information-Based Approach},
	journal = {Annals of EpidemiologyAnn. Epidemiol.},
	volume = {20},
	year = {2010},
	note = {Cited By (since 1996): 2Export Date: 21 November 2012Source: ScopusCODEN: ANNPEdoi: 10.1016/j.annepidem.2010.02.011Language of Original Document: EnglishCorrespondence Address: Costa-Santos, C.; Biostatistics and Medical Informatics Department, Faculty of Medicine, University of Porto, Al. Prof. Hern{\^a}ni Monteiro, 4200-319 Porto, Portugal; email: csantos@med.up.ptReferences: Bland, M., (2000) An introduction to medical statistics, , Oxford University Press, Oxford;Costa Santos, C., Costa Pereira, A., Bernardes, J., Agreement studies in obstetrics and gynecology: inappropriateness, controversies and consequences (2005) Br J Obstet Gynaecol, 112, pp. 667-669; 
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},
	month = {2010///},
	pages = {554 - 561},
	abstract = {Purpose: Disagreement on the interpretation of diagnostic tests and clinical decisions remains an important problem in medicine. As no strategy to assess agreement seems to be fail-safe to compare the degree of agreement, or disagreement, we propose a new information-based approach to assess disagreement. Methods: The sum over all logarithms of possible outcomes of a variable is a valid measure of the amount of information contained in the variable. The proposed measure is based on the amount of information contained in the differences between two observations. This measure is normalized and satisfies the flowing properties: it is a metric, scaled invariant and it has differential weighting. Results: Two real examples and a simulation were used to illustrate the usefulness of the proposed measure to compare the degree of disagreement. Conclusions: Used as complement to the existing methods, we believe our approach can be useful to compare the degree of disagreement among different populations. {\textcopyright} 2010 Elsevier Inc.},
	keywords = {analysis of variance, Apgar score, article, Blood Pressure Determination, blood pressure measurement, correlation coefficient, human, Humans, information science, Information Theory, intermethod comparison, mathematical computing, measurement error, medical research, metric system, Models, Statistical, observer variation, priority journal, probability, process model, reliability, Reproducibility of Results, scale up, standard, Statistical analysis, statistical model, statistics, Statistics as Topic, systolic blood pressure, validity, variance},
	isbn = {10472797 (ISSN)},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-77953667921\&partnerID=40\&md5=2c69deee8cc7bb3a02019dfa464095a1},
	author = {Costa-Santos, C. and Antunes, L. and Souto, A. and Bernardes, J.}
}
@article {2259,
	title = {An intrauterine pressure generator for educational simulation of labour and delivery},
	journal = {Medical Engineering and PhysicsMed. Eng. Phys.},
	volume = {32},
	year = {2010},
	note = {Cited By (since 1996): 3Export Date: 21 November 2012Source: ScopusCODEN: MEPHEdoi: 10.1016/j.medengphy.2010.04.015PubMed ID: 20494606Language of Original Document: EnglishCorrespondence Address: Bastos, L.F.; Instituto de Engenharia Biom{\'e}dica, Divis{\~a}o de Sinal e Imagem, Rua Dr. Roberto Frias, s/n, I302, 4200-465 Porto, Portugal; email: lbastos@fe.up.ptReferences: Carlin, A., Alfirevic, Z., Intrapartum foetal emergencies (2006) Semin Foetal Neonatal Med, 11, pp. 150-157;Draycott, T., Sibanda, T., Owen, L., Akande, V., Winter, C., Reading, S., Does training in obstetric emergencies improve neonatal outcome? (2006) BJOG, 113, pp. 177-182; 
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},
	month = {2010///},
	pages = {740 - 745},
	abstract = {Simulation provides a risk free and controllable environment for training of healthcare providers. The limited realism of available simulators and training programs impedes immersive training in obstetric emergencies. In developed countries, intrapartum monitoring in high-risk cases involves continuous evaluation of foetal heart rate and uterine contractions signals. We present an essential component of a high-fidelity simulator for normal and critical situations in labour and delivery, namely an intrauterine pressure generator. The signal model behind the generator consists of a truncated Gaussian curve with the programmable features: amplitude, frequency, duration, and resting tone. Through analysis of 44. h of physiological data, we demonstrate that the natural variability of these features and of the baseline pressure can be approximated by deterministic trends and stationary stochastic processes. Signal parameters can be controlled by simulation instructors, scripts, or other models to reflect different patients, pathologies, and evolving clinical situations. Twelve 40-min tracings reflecting three different patients in labour were presented to three clinical experts, who attributed similar realism scores to simulated and to real tracings. {\textcopyright} 2010 IPEM.},
	keywords = {article, Clinical situations, Computer simulation, delivery, Delivery, Obstetric, Developed countries, Educational simulations, Essential component, Female, Fetal monitoring, Gaussian curves, generator, Health care providers, Heart Rate, Fetal, Heart rates, High-fidelity simulators, Humans, Immersive, intrauterine pressure, labor, Labor, Obstetric, Labour and delivery, medical education, Medical educational simulation, muscle tone, Natural variability, normal distribution, Obstetrics, Physiological data, Pregnancy, Prenatal Diagnosis, Pressure, Pressure generators, priority journal, Random processes, Risk free, Signal generator, Signal generators, Signal models, Signal parameters, Signal Processing, Computer-Assisted, simulation, Stationary stochastic process, statistical model, statistical parameters, statistics, Stochastic Processes, Time Factors, Training program, Uterine activities, Uterine activity, Uterine Contraction, Uterine Monitoring, uterus contraction},
	isbn = {13504533 (ISSN)},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-77955249563\&partnerID=40\&md5=42013058b547a71f970a3f7f1374caaf},
	author = {Bastos, L.F. and Lobo, M.F. and van Meurs, W.L. and Ayres-de-Campos, D.}
}
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},
	month = {2010///},
	pages = {2698 - 2728},
	abstract = {This letter focuses on the issue of whether risk functionals derived from information-theoretic principles, such as Shannon or R{\'e}nyi{\textquoteright}s entropies, are able to cope with the data classification problem in both the sense of attaining the risk functional minimum and implying the minimum probability of error allowed by the family of functions implemented by the classifier, here denoted by min Pe. The analysis of this so-called minimization of error entropy (MEE) principle is carried out in a single perceptron with continuous activation functions, yielding continuous error distributions. In spite of the fact that the analysis is restricted to single perceptrons, it reveals a large spectrum of behaviors that MEE can be expected to exhibit in both theory and practice. In what concerns the theoretical MEE, our study clarifies the role of the parameters controlling the perceptron activation function (of the squashing type) in often reaching the minimum probability of error. Our study also clarifies the role of the kernel density estimator of the error density in achieving the minimum probability of error in practice. {\textcopyright} 2010 Massachusetts Institute of Technology.},
	keywords = {algorithm, Algorithms, artificial intelligence, artificial neural network, automated pattern recognition, Computer simulation, entropy, letter, Mathematical Concepts, mathematical phenomena, Models, Statistical, Neural Networks (Computer), Pattern Recognition, Automated, standard, statistical model},
	isbn = {08997667 (ISSN)},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-78149334887\&partnerID=40\&md5=97c7445cfa4693d406d979afc4b42319},
	author = {Silva, L.M. and Marques de S{\'a}, J. and Alexandre, L.A.}
}
