86 resultados para fuzzy based evaluation method
Resumo:
Introduction Occupational therapists could play an important role in facilitating driving cessation for ageing drivers. This, however, requires an easy-to-learn, standardised on-road evaluation method. This study therefore investigates whether use of P-drive' could be reliably taught to occupational therapists via a short half-day training session. Method Using the English 26-item version of P-drive, two occupational therapists evaluated the driving ability of 24 home-dwelling drivers aged 70 years or over on a standardised on-road route. Experienced driving instructors' on-road, subjective evaluations were then compared with P-drive scores. Results Following a short half-day training session, P-drive was shown to have almost perfect between-rater reliability (ICC2,1=0.950, 95% CI 0.889 to 0.978). Reliability was stable across sessions including the training phase even if occupational therapists seemed to become slightly less severe in their ratings with experience. P-drive's score was related to the driving instructors' subjective evaluations of driving skills in a non-linear manner (R-2=0.445, p=0.021). Conclusion P-drive is a reliable instrument that can easily be taught to occupational therapists and implemented as a way of standardising the on-road driving test.
Resumo:
The extension of traditional data mining methods to time series has been effectively applied to a wide range of domains such as finance, econometrics, biology, security, and medicine. Many existing mining methods deal with the task of change points detection, but very few provide a flexible approach. Querying specific change points with linguistic variables is particularly useful in crime analysis, where intuitive, understandable, and appropriate detection of changes can significantly improve the allocation of resources for timely and concise operations. In this paper, we propose an on-line method for detecting and querying change points in crime-related time series with the use of a meaningful representation and a fuzzy inference system. Change points detection is based on a shape space representation, and linguistic terms describing geometric properties of the change points are used to express queries, offering the advantage of intuitiveness and flexibility. An empirical evaluation is first conducted on a crime data set to confirm the validity of the proposed method and then on a financial data set to test its general applicability. A comparison to a similar change-point detection algorithm and a sensitivity analysis are also conducted. Results show that the method is able to accurately detect change points at very low computational costs. More broadly, the detection of specific change points within time series of virtually any domain is made more intuitive and more understandable, even for experts not related to data mining.
Resumo:
The aim of this study is to perform a thorough comparison of quantitative susceptibility mapping (QSM) techniques and their dependence on the assumptions made. The compared methodologies were: two iterative single orientation methodologies minimizing the l2, l1TV norm of the prior knowledge of the edges of the object, one over-determined multiple orientation method (COSMOS) and anewly proposed modulated closed-form solution (MCF). The performance of these methods was compared using a numerical phantom and in-vivo high resolution (0.65mm isotropic) brain data acquired at 7T using a new coil combination method. For all QSM methods, the relevant regularization and prior-knowledge parameters were systematically changed in order to evaluate the optimal reconstruction in the presence and absence of a ground truth. Additionally, the QSM contrast was compared to conventional gradient recalled echo (GRE) magnitude and R2* maps obtained from the same dataset. The QSM reconstruction results of the single orientation methods show comparable performance. The MCF method has the highest correlation (corrMCF=0.95, r(2)MCF =0.97) with the state of the art method (COSMOS) with additional advantage of extreme fast computation time. The l-curve method gave the visually most satisfactory balance between reduction of streaking artifacts and over-regularization with the latter being overemphasized when the using the COSMOS susceptibility maps as ground-truth. R2* and susceptibility maps, when calculated from the same datasets, although based on distinct features of the data, have a comparable ability to distinguish deep gray matter structures.
Resumo:
Background: Retrospective analyses suggest that personalized PK-based dosage might be useful for imatinib, as treatment response correlates with trough concentrations (Cmin) in cancer patients. Our objectives were to improve the interpretation of randomly measured concentrations and to confirm its efficiency before evaluating the clinical usefulness of systematic PK-based dosage in chronic myeloid leukemia patients. Methods and Results: A Bayesian method was validated for the prediction of individual Cmin on the basis of a single random observation, and was applied in a prospective multicenter randomized controlled clinical trial. 28 out of 56 patients were enrolled in the systematic dosage individualization arm and had 44 follow-up visits (their clinical follow-up is ongoing). PK-dose-adjustments were proposed in 39% having predicted Cmin significantly away from the target (1000 ng/ml). Recommendations were taken up by physicians in 57%, patients were considered non-compliant in 27%. Median Cmin at study inclusion was 754 ng/ml and differed significantly from the target (p=0.02, Wilcoxon test). On follow-up, Cmin was 984 ng/ml (p=0.82) in the compliant group. CV decreased from 46% to 27% (p=0.02, F-test). Conclusion: PK-based (Bayesian) dosage adjustment is able to bring individual drug exposure closer to a given therapeutic target. Its influence on therapeutic response remains to be evaluated.
Resumo:
To make a comprehensive evaluation of organ-specific out-of-field doses using Monte Carlo (MC) simulations for different breast cancer irradiation techniques and to compare results with a commercial treatment planning system (TPS). Three breast radiotherapy techniques using 6MV tangential photon beams were compared: (a) 2DRT (open rectangular fields), (b) 3DCRT (conformal wedged fields), and (c) hybrid IMRT (open conformal+modulated fields). Over 35 organs were contoured in a whole-body CT scan and organ-specific dose distributions were determined with MC and the TPS. Large differences in out-of-field doses were observed between MC and TPS calculations, even for organs close to the target volume such as the heart, the lungs and the contralateral breast (up to 70% difference). MC simulations showed that a large fraction of the out-of-field dose comes from the out-of-field head scatter fluence (>40%) which is not adequately modeled by the TPS. Based on MC simulations, the 3DCRT technique using external wedges yielded significantly higher doses (up to a factor 4-5 in the pelvis) than the 2DRT and the hybrid IMRT techniques which yielded similar out-of-field doses. In sharp contrast to popular belief, the IMRT technique investigated here does not increase the out-of-field dose compared to conventional techniques and may offer the most optimal plan. The 3DCRT technique with external wedges yields the largest out-of-field doses. For accurate out-of-field dose assessment, a commercial TPS should not be used, even for organs near the target volume (contralateral breast, lungs, heart).
Resumo:
RATIONALE AND OBJECTIVE:. The information assessment method (IAM) permits health professionals to systematically document the relevance, cognitive impact, use and health outcomes of information objects delivered by or retrieved from electronic knowledge resources. The companion review paper (Part 1) critically examined the literature, and proposed a 'Push-Pull-Acquisition-Cognition-Application' evaluation framework, which is operationalized by IAM. The purpose of the present paper (Part 2) is to examine the content validity of the IAM cognitive checklist when linked to email alerts. METHODS: A qualitative component of a mixed methods study was conducted with 46 doctors reading and rating research-based synopses sent on email. The unit of analysis was a doctor's explanation of a rating of one item regarding one synopsis. Interviews with participants provided 253 units that were analysed to assess concordance with item definitions. RESULTS AND CONCLUSION: The content relevance of seven items was supported. For three items, revisions were needed. Interviews suggested one new item. This study has yielded a 2008 version of IAM.
Resumo:
Aim Recently developed parametric methods in historical biogeography allow researchers to integrate temporal and palaeogeographical information into the reconstruction of biogeographical scenarios, thus overcoming a known bias of parsimony-based approaches. Here, we compare a parametric method, dispersal-extinction-cladogenesis (DEC), against a parsimony-based method, dispersal-vicariance analysis (DIVA), which does not incorporate branch lengths but accounts for phylogenetic uncertainty through a Bayesian empirical approach (Bayes-DIVA). We analyse the benefits and limitations of each method using the cosmopolitan plant family Sapindaceae as a case study.Location World-wide.Methods Phylogenetic relationships were estimated by Bayesian inference on a large dataset representing generic diversity within Sapindaceae. Lineage divergence times were estimated by penalized likelihood over a sample of trees from the posterior distribution of the phylogeny to account for dating uncertainty in biogeographical reconstructions. We compared biogeographical scenarios between Bayes-DIVA and two different DEC models: one with no geological constraints and another that employed a stratified palaeogeographical model in which dispersal rates were scaled according to area connectivity across four time slices, reflecting the changing continental configuration over the last 110 million years.Results Despite differences in the underlying biogeographical model, Bayes-DIVA and DEC inferred similar biogeographical scenarios. The main differences were: (1) in the timing of dispersal events - which in Bayes-DIVA sometimes conflicts with palaeogeographical information, and (2) in the lower frequency of terminal dispersal events inferred by DEC. Uncertainty in divergence time estimations influenced both the inference of ancestral ranges and the decisiveness with which an area can be assigned to a node.Main conclusions By considering lineage divergence times, the DEC method gives more accurate reconstructions that are in agreement with palaeogeographical evidence. In contrast, Bayes-DIVA showed the highest decisiveness in unequivocally reconstructing ancestral ranges, probably reflecting its ability to integrate phylogenetic uncertainty. Care should be taken in defining the palaeogeographical model in DEC because of the possibility of overestimating the frequency of extinction events, or of inferring ancestral ranges that are outside the extant species ranges, owing to dispersal constraints enforced by the model. The wide-spanning spatial and temporal model proposed here could prove useful for testing large-scale biogeographical patterns in plants.
Resumo:
PURPOSE: Few studies compare the variabilities that characterize environmental (EM) and biological monitoring (BM) data. Indeed, comparing their respective variabilities can help to identify the best strategy for evaluating occupational exposure. The objective of this study is to quantify the biological variability associated with 18 bio-indicators currently used in work environments. METHOD: Intra-individual (BV(intra)), inter-individual (BV(inter)), and total biological variability (BV(total)) were quantified using validated physiologically based toxicokinetic (PBTK) models coupled with Monte Carlo simulations. Two environmental exposure profiles with different levels of variability were considered (GSD of 1.5 and 2.0). RESULTS: PBTK models coupled with Monte Carlo simulations were successfully used to predict the biological variability of biological exposure indicators. The predicted values follow a lognormal distribution, characterized by GSD ranging from 1.1 to 2.3. Our results show that there is a link between biological variability and the half-life of bio-indicators, since BV(intra) and BV(total) both decrease as the biological indicator half-lives increase. BV(intra) is always lower than the variability in the air concentrations. On an individual basis, this means that the variability associated with the measurement of biological indicators is always lower than the variability characterizing airborne levels of contaminants. For a group of workers, BM is less variable than EM for bio-indicators with half-lives longer than 10-15 h. CONCLUSION: The variability data obtained in the present study can be useful in the development of BM strategies for exposure assessment and can be used to calculate the number of samples required for guiding industrial hygienists or medical doctors in decision-making.
Resumo:
OBJECTIVE: To extract and to validate a brief version of the DISCERN which could identify mental health-related websites with good content quality. METHOD: The present study is based on the analysis of data issued from six previous studies which used DISCERN and a standardized tool for the evaluation of content quality (evidence-based health information) of 388 mental health-related websites. After extracting the Brief DISCERN, several psychometric properties (content validity through a Factor analysis, internal consistency by the Cronbach's alpha index, predictive validity through the diagnostic tests, concurrent validity by the strength of association between the Brief DISCERN and the original DISCERN scores) were investigated to ascertain its general applicability. RESULTS: A Brief DISCERN composed of two factors and six items was extracted from the original 16 items version of the DISCERN. Cronbach's alpha coefficients were more than acceptable for the complete questionnaire (alpha=0.74) and for the two distinct domains: treatments information (alpha=0.87) and reliability (alpha=0.83). Sensibility and specificity of the Brief DISCERN cut-off score > or =16 in the detection of good content quality websites were 0.357 and 0.945, respectively. Its predictive positive and negative values were 0.98 and 0.83, respectively. A statistically significant linear correlation was found between the total scores of the Brief DISCERN and those of the original DISCERN (r=0.84 and p<0.0005). CONCLUSION: The Brief DISCERN seems to be a reliable and valid instrument able to discriminate between websites with good and poor content quality. PRACTICE IMPLICATIONS: The Brief DISCERN is a simple tool which could facilitate the identification of good information on the web by patients and general consumers.
Resumo:
Health assessment and medical surveillance of workers exposed to combustion nanoparticles are challenging. The aim was to evaluate the feasibility of using exhaled breath condensate (EBC) from healthy volunteers for (1) assessing the lung deposited dose of combustion nanoparticles and (2) determining the resulting oxidative stress by measuring hydrogen peroxide (H2O2) and malondialdehyde (MDA). Methods: Fifteen healthy nonsmoker volunteers were exposed to three different levels of sidestream cigarette smoke under controlled conditions. EBC was repeatedly collected before, during, and 1 and 2 hr after exposure. Exposure variables were measured by direct reading instruments and by active sampling. The different EBC samples were analyzed for particle number concentration (light-scattering-based method) and for selected compounds considered oxidative stress markers. Results: Subjects were exposed to an average airborne concentration up to 4.3×10(5) particles/cm(3) (average geometric size ∼60-80 nm). Up to 10×10(8) particles/mL could be measured in the collected EBC with a broad size distribution (50(th) percentile ∼160 nm), but these biological concentrations were not related to the exposure level of cigarette smoke particles. Although H2O2 and MDA concentrations in EBC increased during exposure, only H2O2 showed a transient normalization 1 hr after exposure and increased afterward. In contrast, MDA levels stayed elevated during the 2 hr post exposure. Conclusions: The use of diffusion light scattering for particle counting proved to be sufficiently sensitive to detect objects in EBC, but lacked the specificity for carbonaceous tobacco smoke particles. Our results suggest two phases of oxidation markers in EBC: first, the initial deposition of particles and gases in the lung lining liquid, and later the start of oxidative stress with associated cell membrane damage. Future studies should extend the follow-up time and should remove gases or particles from the air to allow differentiation between the different sources of H2O2 and MDA.
Resumo:
BACKGROUND: Cone-beam computed tomography (CBCT) image-guided radiotherapy (IGRT) systems are widely used tools to verify and correct the target position before each fraction, allowing to maximize treatment accuracy and precision. In this study, we evaluate automatic three-dimensional intensity-based rigid registration (RR) methods for prostate setup correction using CBCT scans and study the impact of rectal distension on registration quality. METHODS: We retrospectively analyzed 115 CBCT scans of 10 prostate patients. CT-to-CBCT registration was performed using (a) global RR, (b) bony RR, or (c) bony RR refined by a local prostate RR using the CT clinical target volume (CTV) expanded with 1-to-20-mm varying margins. After propagation of the manual CT contours, automatic CBCT contours were generated. For evaluation, a radiation oncologist manually delineated the CTV on the CBCT scans. The propagated and manual CBCT contours were compared using the Dice similarity and a measure based on the bidirectional local distance (BLD). We also conducted a blind visual assessment of the quality of the propagated segmentations. Moreover, we automatically quantified rectal distension between the CT and CBCT scans without using the manual CBCT contours and we investigated its correlation with the registration failures. To improve the registration quality, the air in the rectum was replaced with soft tissue using a filter. The results with and without filtering were compared. RESULTS: The statistical analysis of the Dice coefficients and the BLD values resulted in highly significant differences (p<10(-6)) for the 5-mm and 8-mm local RRs vs the global, bony and 1-mm local RRs. The 8-mm local RR provided the best compromise between accuracy and robustness (Dice median of 0.814 and 97% of success with filtering the air in the rectum). We observed that all failures were due to high rectal distension. Moreover, the visual assessment confirmed the superiority of the 8-mm local RR over the bony RR. CONCLUSION: The most successful CT-to-CBCT RR method proved to be the 8-mm local RR. We have shown the correlation between its registration failures and rectal distension. Furthermore, we have provided a simple (easily applicable in routine) and automatic method to quantify rectal distension and to predict registration failure using only the manual CT contours.
Resumo:
Waveform tomographic imaging of crosshole georadar data is a powerful method to investigate the shallow subsurface because of its ability to provide images of pertinent petrophysical parameters with extremely high spatial resolution. All current crosshole georadar waveform inversion strategies are based on the assumption of frequency-independent electromagnetic constitutive parameters. However, in reality, these parameters are known to be frequency-dependent and complex and thus recorded georadar data may show significant dispersive behavior. In this paper, we evaluate synthetically the reconstruction limits of a recently published crosshole georadar waveform inversion scheme in the presence of varying degrees of dielectric dispersion. Our results indicate that, when combined with a source wavelet estimation procedure that provides a means of partially accounting for the frequency-dependent effects through an "effective" wavelet, the inversion algorithm performs remarkably well in weakly to moderately dispersive environments and has the ability to provide adequate tomographic reconstructions.
Resumo:
The identification and quantification of proteins and lipids is of major importance for the diagnosis, prognosis and understanding of the molecular mechanisms involved in disease development. Owing to its selectivity and sensitivity, mass spectrometry has become a key technique in analytical platforms for proteomic and lipidomic investigations. Using this technique, many strategies have been developed based on unbiased or targeted approaches to highlight or monitor molecules of interest from biomatrices. Although these approaches have largely been employed in cancer research, this type of investigation has been met by a growing interest in the field of cardiovascular disorders, potentially leading to the discovery of novel biomarkers and the development of new therapies. In this paper, we will review the different mass spectrometry-based proteomic and lipidomic strategies applied in cardiovascular diseases, especially atherosclerosis. Particular attention will be given to recent developments and the role of bioinformatics in data treatment. This review will be of broad interest to the medical community by providing a tutorial of how mass spectrometric strategies can support clinical trials.
Resumo:
Matrix effects, which represent an important issue in liquid chromatography coupled to mass spectrometry or tandem mass spectrometry detection, should be closely assessed during method development. In the case of quantitative analysis, the use of stable isotope-labelled internal standard with physico-chemical properties and ionization behaviour similar to the analyte is recommended. In this paper, an example of the choice of a co-eluting deuterated internal standard to compensate for short-term and long-term matrix effect in the case of chiral (R,S)-methadone plasma quantification is reported. The method was fully validated over a concentration range of 5-800 ng/mL for each methadone enantiomer with satisfactory relative bias (-1.0 to 1.0%), repeatability (0.9-4.9%) and intermediate precision (1.4-12.0%). From the results obtained during validation, a control chart process during 52 series of routine analysis was established using both intermediate precision standard deviation and FDA acceptance criteria. The results of routine quality control samples were generally included in the +/-15% variability around the target value and mainly in the two standard deviation interval illustrating the long-term stability of the method. The intermediate precision variability estimated in method validation was found to be coherent with the routine use of the method. During this period, 257 trough concentration and 54 peak concentration plasma samples of patients undergoing (R,S)-methadone treatment were successfully analysed for routine therapeutic drug monitoring.
Resumo:
MOTIVATION: Microarray results accumulated in public repositories are widely reused in meta-analytical studies and secondary databases. The quality of the data obtained with this technology varies from experiment to experiment, and an efficient method for quality assessment is necessary to ensure their reliability. RESULTS: The lack of a good benchmark has hampered evaluation of existing methods for quality control. In this study, we propose a new independent quality metric that is based on evolutionary conservation of expression profiles. We show, using 11 large organ-specific datasets, that IQRray, a new quality metrics developed by us, exhibits the highest correlation with this reference metric, among 14 metrics tested. IQRray outperforms other methods in identification of poor quality arrays in datasets composed of arrays from many independent experiments. In contrast, the performance of methods designed for detecting outliers in a single experiment like Normalized Unscaled Standard Error and Relative Log Expression was low because of the inability of these methods to detect datasets containing only low-quality arrays and because the scores cannot be directly compared between experiments. AVAILABILITY AND IMPLEMENTATION: The R implementation of IQRray is available at: ftp://lausanne.isb-sib.ch/pub/databases/Bgee/general/IQRray.R. CONTACT: Marta.Rosikiewicz@unil.ch SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.