Sistema de apoio à decisão clínica: quality of life system

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

The results of the Campaign for evaluating sphygmomanometers accuracy and their physical conditions

OBJECTIVE: To evaluate the sphygmomanometers calibration accuracy and the physical conditions of the cuff-bladder, bulb, pump, and valve. METHODS: Sixty hundred and forty five aneroid sphygmomanometers were evaluated, 521 used in private practice and 124 used in hospitals. Aneroid manometers were tested against a properly calibrated mercury manometer and were considered calibrated when the error was <=3mm Hg. The physical conditions of the cuffs-bladder, bulb, pump, and valve were also evaluated. RESULTS: Of the aneroid sphygmomanometers tested, 51% of those used in private practice and 56% of those used in hospitals were found to be not accurately calibrated. Of these, the magnitude of inaccuracy ranged from 4 to 8mm Hg in 70% and 51% of the devices, respectively. The problems found in the cuffs - bladders, bulbs, pumps, and valves of the private practice and hospital devices were bladder damage (34% vs. 21%, respectively), holes/leaks in the bulbs (22% vs. 4%, respectively), and rubber aging (15% vs. 12%, respectively). Of the devices tested, 72% revealed at least one problem interfering with blood pressure measurement accuracy. CONCLUSION: Most of the manometers evaluated, whether used in private practice or in hospitals, were found to be inaccurate and unreliable, and their use may jeopardize the diagnosis and treatment of arterial hypertension.

Hypertension and clustering of cardiovascular risk factors in a community in Southeast Brazil: the Bambuí Health and Ageing Study

OBJECTIVE - A population-based prospective study was analysed to: a) determine the prevalence of hypertension; b) investigate the clustering of other cardiovascular risk factors and c) verify whether older differed from younger adults in the pattern of clustering. METHODS - The data comprised a representative sample of the population of Bambuí, Brazil. Multiple logistic regression was used to investigate the independent association between hypertension and selected factors. RESULTS - A total of 820 younger adults (82.5%) and 1494 older adults (85.9%) participated in this study. The overall prevalence of hypertension was 24.8% (SE=1.4 %), being higher in women (26.9±1.5%) than in men (22.0± 1.7%) (p=0.033). Hypertension was positively and significantly associated with physical inactivity, overweight, hypercholesterolemia hyperglycemia and hypertriglyceridemia. The coexistence of hypertension with 4 or more of these risk factors occurred 6 times more than expected by chance, after adjusting for age and sex (OR=6.3; 95%CI: 3.4-11.9). The pattern of risk factor clustering in hypertensive individuals differed with age. CONCLUSION - Our results reinforce the need to increase detection and treatment of hypertension and to approach patients' global risk profiles.

The importance and accuracy of wind power forecasts

Due to the global crisis o f climate change many countries throughout the world are installing the renewable energy o f wind power into their electricity system. Wind energy causes complications when it is being integrated into the electricity system due its intermittent nature. Additionally winds intennittency can result in penalties being enforced due to the deregulation in the electricity market. Wind power forecasting can play a pivotal role to ease the integration o f wind energy. Wind power forecasts at 24 and 48 hours ahead of time are deemed the most crucial for determining an appropriate balance on the power system. In the electricity market wind power forecasts can also assist market participants in terms o f applying a suitable bidding strategy, unit commitment or have an impact on the value o f the spot price. For these reasons this study investigates the importance o f wind power forecasts for such players as the Transmission System Operators (TSOs) and Independent Power Producers (IPPs). Investigation in this study is also conducted into the impacts that wind power forecasts can have on the electricity market in relation to bidding strategies, spot price and unit commitment by examining various case studies. The results o f these case studies portray a clear and insightful indication o f the significance o f availing from the information available from wind power forecasts. The accuracy o f a particular wind power forecast is also explored. Data from a wind power forecast is examined in the circumstances o f both 24 and 48 hour forecasts. The accuracy o f the wind power forecasts are displayed through a variety o f statistical approaches. The results o f the investigation can assist market participants taking part in the electricity pool and also provides a platform that can be applied to any forecast when attempting to define its accuracy. This study contributes significantly to the knowledge in the area o f wind power forecasts by explaining the importance o f wind power forecasting within the energy sector. It innovativeness and uniqueness lies in determining the accuracy o f a particular wind power forecast that was previously unknown.

Objective function based fuzzy clustering in air traffic management

Data analysis, fuzzy clustering, fuzzy rules, air traffic management

Prototype-based classification and clustering

Magdeburg, Univ., Fak. für Informatik, Habil.-Schr., 2006

Visual analysis, clustering, and classification of contrast-enhanced tumor perfusion MRI data

Magdeburg, Univ., Fak. für Inf., Diss., 2014

Prototype based clustering in high-dimensional feature spaces

...In dieser Arbeit untersuche ich den ”Fluch der Dimensionen” mittels dem Begriff der Distanzkonzentration. Ich zeige, dass dieser Effekt im Datenmodell mittels der paarweisen Kovarianzkoeffizienten der Randverteilungen beschrieben werden kann. Zusätzlich vergleiche ich 10 prototypbasierte Clusteralgorithmen mittels 800.000 Clusterergebnissen von künstlich erzeugten Datensätzen. Ich erforsche, wie und warum Clusteralgorithmen von der Anzahl der Merkmale beeinflusst werden. Mit den Clusterergebnissen untersuche ich außerdem, wie gut 5 der populärsten Clusterqualitätsmaße die tatsächliche Clusterqualität schätzen.

Accuracy vs. simplicity: a complex trade-off

Inductive learning aims at finding general rules that hold true in a database. Targeted learning seeks rules for the predictions of the value of a variable based on the values of others, as in the case of linear or non-parametric regression analysis. Non-targeted learning finds regularities without a specific prediction goal. We model the product of non-targeted learning as rules that state that a certain phenomenon never happens, or that certain conditions necessitate another. For all types of rules, there is a trade-off between the rule's accuracy and its simplicity. Thus rule selection can be viewed as a choice problem, among pairs of degree of accuracy and degree of complexity. However, one cannot in general tell what is the feasible set in the accuracy-complexity space. Formally, we show that finding out whether a point belongs to this set is computationally hard. In particular, in the context of linear regression, finding a small set of variables that obtain a certain value of R2 is computationally hard. Computational complexity may explain why a person is not always aware of rules that, if asked, she would find valid. This, in turn, may explain why one can change other people's minds (opinions, beliefs) without providing new information.

Segmentation and Clustering of Textual Sequences: a Typological Approach

The long term goal of this research is to develop a program able to produce an automatic segmentation and categorization of textual sequences into discourse types. In this preliminary contribution, we present the construction of an algorithm which takes a segmented text as input and attempts to produce a categorization of sequences, such as narrative, argumentative, descriptive and so on. Also, this work aims at investigating a possible convergence between the typological approach developed in particular in the field of text and discourse analysis in French by Adam (2008) and Bronckart (1997) and unsupervised statistical learning.

Octopus Standard Automated Perimetry, Pulsar Perimetry, Moorfields Motion Displacement Test and Heidelberg Retinal Tomography in Glaucoma Detection - A Comparison of Diagnostic Accuracy

Purpose: To investigate the accuracy of 4 clinical instruments in the detection of glaucomatous damage. Methods: 102 eyes of 55 test subjects (Age mean = 66.5yrs, range = [39; 89]) underwent Heidelberg Retinal Tomography (HRTIII), (disc area<2.43); and standard automated perimetry (SAP) using Octopus (Dynamic); Pulsar (TOP); and Moorfields Motion Displacement Test (MDT) (ESTA strategy). Eyes were separated into three groups 1) Healthy (H): IOP<21mmHg and healthy discs (clinical examination), 39 subjects, 78 eyes; 2) Glaucoma suspect (GS): Suspicious discs (clinical examination), 12 subjects, 15 eyes; 3) Glaucoma (G): progressive structural or functional loss, 14 subjects, 20 eyes. Clinical diagnostic precision was examined using the cut-off associated with the p<5% normative limit of MD (Octopus/Pulsar), PTD (MDT) and MRA (HRT) analysis. The sensitivity, specificity and accuracy were calculated for each instrument. Results: See table Conclusions: Despite the advantage of defining glaucoma suspects using clinical optic disc examination, the HRT did not yield significantly higher accuracy than functional measures. HRT, MDT and Octopus SAP yielded higher accuracy than Pulsar perimetry, although results did not reach statistical significance. Further studies are required to investigate the structure-function correlations between these instruments.

Kernels semàntics per a clustering de patrons

Memòria elaborada a partir d’una estada al projecte Proteus de la New York University entre abril i juny del 2007. Les tècniques de clustering poden ajudar a reduir la supervisió en processos d’obtenció de patrons per a Extracció d’Informació. Tanmateix, és necessari disposar d’algorismes adequats a documents, i aquests algorismes requereixen mesures adequades de similitud entre patrons. Els kernels poden oferir una solució a aquests problemes, però l’aprenentatge no supervisat requereix d’estrat`egies m´es astutes que l’aprenentatge supervisat per a incorporar major quantitat d’informació. En aquesta memòria, fruit de la meva estada de mes d’Abril al de Juny de 2007 al projecte. Proteus de la New York University, es proposen i avaluen diversos kernels sobre patrons. Ini- cialment s’estudien kernels amb una família de patrons restringits, i a continuació s’apliquen kernels ja usats en tasques supervisades d’Extracció d’Informació. Degut a la degradació del rendiment que experimenta el clustering a l’afegir informació irrellevant, els kernels se simpli- fiquen i es busquen estratègies per a incorporar-hi semàntica de forma selectiva. Finalment, s’estudia quin efecte té aplicar clustering sobre el coneixement semàntic com a pas previ al clustering de patrons. Les diverses estratègies s’avaluen en tasques de clustering de documents i patrons usant dades reals.

Accuracy of Brain Multimodal Monitoring to Detect Cerebral Hypoperfusion After Traumatic Brain Injury.

OBJECTIVE:: To examine the accuracy of brain multimodal monitoring-consisting of intracranial pressure, brain tissue PO2, and cerebral microdialysis-in detecting cerebral hypoperfusion in patients with severe traumatic brain injury. DESIGN:: Prospective single-center study. PATIENTS:: Patients with severe traumatic brain injury. SETTING:: Medico-surgical ICU, university hospital. INTERVENTION:: Intracranial pressure, brain tissue PO2, and cerebral microdialysis monitoring (right frontal lobe, apparently normal tissue) combined with cerebral blood flow measurements using perfusion CT. MEASUREMENTS AND MAIN RESULTS:: Cerebral blood flow was measured using perfusion CT in tissue area around intracranial monitoring (regional cerebral blood flow) and in bilateral supra-ventricular brain areas (global cerebral blood flow) and was matched to cerebral physiologic variables. The accuracy of intracranial monitoring to predict cerebral hypoperfusion (defined as an oligemic regional cerebral blood flow < 35 mL/100 g/min) was examined using area under the receiver-operating characteristic curves. Thirty perfusion CT scans (median, 27 hr [interquartile range, 20-45] after traumatic brain injury) were performed on 27 patients (age, 39 yr [24-54 yr]; Glasgow Coma Scale, 7 [6-8]; 24/27 [89%] with diffuse injury). Regional cerebral blood flow correlated significantly with global cerebral blood flow (Pearson r = 0.70, p < 0.01). Compared with normal regional cerebral blood flow (n = 16), low regional cerebral blood flow (n = 14) measurements had a higher proportion of samples with intracranial pressure more than 20 mm Hg (13% vs 30%), brain tissue PO2 less than 20 mm Hg (9% vs 20%), cerebral microdialysis glucose less than 1 mmol/L (22% vs 57%), and lactate/pyruvate ratio more than 40 (4% vs 14%; all p < 0.05). Compared with intracranial pressure monitoring alone (area under the receiver-operating characteristic curve, 0.74 [95% CI, 0.61-0.87]), monitoring intracranial pressure + brain tissue PO2 (area under the receiver-operating characteristic curve, 0.84 [0.74-0.93]) or intracranial pressure + brain tissue PO2+ cerebral microdialysis (area under the receiver-operating characteristic curve, 0.88 [0.79-0.96]) was significantly more accurate in predicting low regional cerebral blood flow (both p < 0.05). CONCLUSION:: Brain multimodal monitoring-including intracranial pressure, brain tissue PO2, and cerebral microdialysis-is more accurate than intracranial pressure monitoring alone in detecting cerebral hypoperfusion at the bedside in patients with severe traumatic brain injury and predominantly diffuse injury.

Accuracy of a new transmittance-reflectance pulse oximetry sensor in critically ill neonates.

OBJECTIVE: To test the accuracy of a new pulse oximeter sensor based on transmittance and reflectance. This sensor makes transillumination of tissue unnecessary and allows measurements on the hand, forearm, foot, and lower limb. DESIGN: Prospective, open, nonrandomized criterion standard study. SETTING: Neonatal intensive care unit, tertiary care center. PATIENTS: Sequential sample of 54 critically ill neonates (gestational age 27 to 42 wks; postnatal age 1 to 28 days) with arterial catheters in place. MEASUREMENTS AND MAIN RESULTS: A total of 99 comparisons between pulse oximetry and arterial saturation were obtained. Comparison of femoral or umbilical arterial blood with transcutaneous measurements on the lower limb (n = 66) demonstrated an excellent correlation (r2 = .96). The mean difference was +1.44% +/- 3.51 (SD) % (range -11% to +8%). Comparison of the transcutaneous values with the radial artery saturation from the corresponding upper limb (n = 33) revealed a correlation coefficient of 0.94 with a mean error of +0.66% +/- 3.34% (range -6% to +7%). The mean difference between noninvasive and invasive measurements was least with the test sensor on the hand, intermediate on the calf and arm, and greatest on the foot. The mean error and its standard deviation were slightly larger for arterial saturation values < 90% than for values > or = 90%. CONCLUSION: Accurate pulse oximetry saturation can be acquired from the hand, forearm, foot, and calf of critically ill newborns using this new sensor.

Effect of training-sample size and classification difficulty on the accuracy of genomic predictors.

Introduction: As part of the MicroArray Quality Control (MAQC)-II project, this analysis examines how the choice of univariate feature-selection methods and classification algorithms may influence the performance of genomic predictors under varying degrees of prediction difficulty represented by three clinically relevant endpoints. Methods: We used gene-expression data from 230 breast cancers (grouped into training and independent validation sets), and we examined 40 predictors (five univariate feature-selection methods combined with eight different classifiers) for each of the three endpoints. Their classification performance was estimated on the training set by using two different resampling methods and compared with the accuracy observed in the independent validation set. Results: A ranking of the three classification problems was obtained, and the performance of 120 models was estimated and assessed on an independent validation set. The bootstrapping estimates were closer to the validation performance than were the cross-validation estimates. The required sample size for each endpoint was estimated, and both gene-level and pathway-level analyses were performed on the obtained models. Conclusions: We showed that genomic predictor accuracy is determined largely by an interplay between sample size and classification difficulty. Variations on univariate feature-selection methods and choice of classification algorithm have only a modest impact on predictor performance, and several statistically equally good predictors can be developed for any given classification problem.