943 resultados para detection rate


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Traffic incidents are non-recurring events that can cause a temporary reduction in roadway capacity. They have been recognized as a major contributor to traffic congestion on our nation’s highway systems. To alleviate their impacts on capacity, automatic incident detection (AID) has been applied as an incident management strategy to reduce the total incident duration. AID relies on an algorithm to identify the occurrence of incidents by analyzing real-time traffic data collected from surveillance detectors. Significant research has been performed to develop AID algorithms for incident detection on freeways; however, similar research on major arterial streets remains largely at the initial stage of development and testing. This dissertation research aims to identify design strategies for the deployment of an Artificial Neural Network (ANN) based AID algorithm for major arterial streets. A section of the US-1 corridor in Miami-Dade County, Florida was coded in the CORSIM microscopic simulation model to generate data for both model calibration and validation. To better capture the relationship between the traffic data and the corresponding incident status, Discrete Wavelet Transform (DWT) and data normalization were applied to the simulated data. Multiple ANN models were then developed for different detector configurations, historical data usage, and the selection of traffic flow parameters. To assess the performance of different design alternatives, the model outputs were compared based on both detection rate (DR) and false alarm rate (FAR). The results show that the best models were able to achieve a high DR of between 90% and 95%, a mean time to detect (MTTD) of 55-85 seconds, and a FAR below 4%. The results also show that a detector configuration including only the mid-block and upstream detectors performs almost as well as one that also includes a downstream detector. In addition, DWT was found to be able to improve model performance, and the use of historical data from previous time cycles improved the detection rate. Speed was found to have the most significant impact on the detection rate, while volume was found to contribute the least. The results from this research provide useful insights on the design of AID for arterial street applications.

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Traffic incidents are non-recurring events that can cause a temporary reduction in roadway capacity. They have been recognized as a major contributor to traffic congestion on our national highway systems. To alleviate their impacts on capacity, automatic incident detection (AID) has been applied as an incident management strategy to reduce the total incident duration. AID relies on an algorithm to identify the occurrence of incidents by analyzing real-time traffic data collected from surveillance detectors. Significant research has been performed to develop AID algorithms for incident detection on freeways; however, similar research on major arterial streets remains largely at the initial stage of development and testing. This dissertation research aims to identify design strategies for the deployment of an Artificial Neural Network (ANN) based AID algorithm for major arterial streets. A section of the US-1 corridor in Miami-Dade County, Florida was coded in the CORSIM microscopic simulation model to generate data for both model calibration and validation. To better capture the relationship between the traffic data and the corresponding incident status, Discrete Wavelet Transform (DWT) and data normalization were applied to the simulated data. Multiple ANN models were then developed for different detector configurations, historical data usage, and the selection of traffic flow parameters. To assess the performance of different design alternatives, the model outputs were compared based on both detection rate (DR) and false alarm rate (FAR). The results show that the best models were able to achieve a high DR of between 90% and 95%, a mean time to detect (MTTD) of 55-85 seconds, and a FAR below 4%. The results also show that a detector configuration including only the mid-block and upstream detectors performs almost as well as one that also includes a downstream detector. In addition, DWT was found to be able to improve model performance, and the use of historical data from previous time cycles improved the detection rate. Speed was found to have the most significant impact on the detection rate, while volume was found to contribute the least. The results from this research provide useful insights on the design of AID for arterial street applications.

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In a European BIOMED-2 collaborative study, multiplex PCR assays have successfully been developed and standardized for the detection of clonally rearranged immunoglobulin (Ig) and T-cell receptor (TCR) genes and the chromosome aberrations t(11;14) and t(14;18). This has resulted in 107 different primers in only 18 multiplex PCR tubes: three VH-JH, two DH-JH, two Ig kappa (IGK), one Ig lambda (IGL), three TCR beta (TCRB), two TCR gamma (TCRG), one TCR delta (TCRD), three BCL1-Ig heavy chain (IGH), and one BCL2-IGH. The PCR products of Ig/TCR genes can be analyzed for clonality assessment by heteroduplex analysis or GeneScanning. The detection rate of clonal rearrangements using the BIOMED-2 primer sets is unprecedentedly high. This is mainly based on the complementarity of the various BIOMED-2 tubes. In particular, combined application of IGH (VH-JH and DH-JH) and IGK tubes can detect virtually all clonal B-cell proliferations, even in B-cell malignancies with high levels of somatic mutations. The contribution of IGL gene rearrangements seems limited. Combined usage of the TCRB and TCRG tubes detects virtually all clonal T-cell populations, whereas the TCRD tube has added value in case of TCRgammadelta(+) T-cell proliferations. The BIOMED-2 multiplex tubes can now be used for diagnostic clonality studies as well as for the identification of PCR targets suitable for the detection of minimal residual disease.

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[EN]This paper describes a face detection system which goes beyond traditional approaches normally designed for still images. First the video stream context is considered to apply the detector, and therefore, the resulting system is designed taking into consideration a main feature available in a video stream, i.e. temporal coherence. The resulting system builds a feature based model for each detected face, and searches them using various model information in the next frame. The results achieved for video stream processing outperform Rowley-Kanade's and Viola-Jones' solutions providing eye and face data in a reduced time with a notable correct detection rate.

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Objective: Phenobarbital increases electroclinical uncoupling and our preliminary observations suggest it may also affect electrographic seizure morphology. This may alter the performance of a novel seizure detection algorithm (SDA) developed by our group. The objectives of this study were to compare the morphology of seizures before and after phenobarbital administration in neonates and to determine the effect of any changes on automated seizure detection rates. Methods: The EEGs of 18 term neonates with seizures both pre- and post-phenobarbital (524 seizures) administration were studied. Ten features of seizures were manually quantified and summary measures for each neonate were statistically compared between pre- and post-phenobarbital seizures. SDA seizure detection rates were also compared. Results: Post-phenobarbital seizures showed significantly lower amplitude (p < 0.001) and involved fewer EEG channels at the peak of seizure (p < 0.05). No other features or SDA detection rates showed a statistical difference. Conclusion: These findings show that phenobarbital reduces both the amplitude and propagation of seizures which may help to explain electroclinical uncoupling of seizures. The seizure detection rate of the algorithm was unaffected by these changes. Significance: The results suggest that users should not need to adjust the SDA sensitivity threshold after phenobarbital administration.

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Background Little information is available on the prevalence of depression in Malawi in primary health care settings and yet there is increased number of cases of depression presenting at tertiary level in severe form. Aim The aim of the study was to determine the prevalence of depression among patients and its detection by health care workers at a primary health care clinic in Zomba. Methods A cross-sectional survey was done among patients attending outpatient department at Matawale Health Centre, in Zomba from 1st July 2009 through to 31st July 2009. A total of 350 adults were randomly selected using systematic sampling. The “Self Reporting Questionnaire”, a questionnaire measuring social demographic factors and the Structured Clinical Interview for DSM-IV Axis I disorders Non-Patient Version (SCID-NP) were administered verbally to the participants. Findings The prevalence of depression among the patients attending the outpatients department was found to be 30.3% while detection rate of depression by clinician was 0%. Conclusion The results revealed the magnitude of depression which is prevalent in the primary health care clinic that goes undiagnosed and unmanaged. It is therefore recommended that primary health care providers do thorough assessments to address common mental disorders especially depression and they should be educated to recognise and manage depression appropriately at primary care level.

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Prostate cancer is the most common non-dermatological cancer amongst men in the developed world. The current definitive diagnosis is core needle biopsy guided by transrectal ultrasound. However, this method suffers from low sensitivity and specificity in detecting cancer. Recently, a new ultrasound based tissue typing approach has been proposed, known as temporal enhanced ultrasound (TeUS). In this approach, a set of temporal ultrasound frames is collected from a stationary tissue location without any intentional mechanical excitation. The main aim of this thesis is to implement a deep learning-based solution for prostate cancer detection and grading using TeUS data. In the proposed solution, convolutional neural networks are trained to extract high-level features from time domain TeUS data in temporally and spatially adjacent frames in nine in vivo prostatectomy cases. This approach avoids information loss due to feature extraction and also improves cancer detection rate. The output likelihoods of two TeUS arrangements are then combined to form our novel decision support system. This deep learning-based approach results in the area under the receiver operating characteristic curve (AUC) of 0.80 and 0.73 for prostate cancer detection and grading, respectively, in leave-one-patient-out cross-validation. Recently, multi-parametric magnetic resonance imaging (mp-MRI) has been utilized to improve detection rate of aggressive prostate cancer. In this thesis, for the first time, we present the fusion of mp-MRI and TeUS for characterization of prostate cancer to compensates the deficiencies of each image modalities and improve cancer detection rate. The results obtained using TeUS are fused with those attained using consolidated mp-MRI maps from multiple MR modalities and cancer delineations on those by multiple clinicians. The proposed fusion approach yields the AUC of 0.86 in prostate cancer detection. The outcomes of this thesis emphasize the viable potential of TeUS as a tissue typing method. Employing this ultrasound-based intervention, which is non-invasive and inexpensive, can be a valuable and practical addition to enhance the current prostate cancer detection.

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Descrição do comportamento e análise da tendência da hanseníase entre pacientes residentes no Estado do Espírito Santo, Brasil, de 1980 a 2003. Utilizando modelos estatísticos para séries temporais, identificou-se tendência crescente para todo o período da taxa de detecção global (p < 0,05) com aparente estabilização no final do período, verificamos também tendência crescente para os períodos: (i) 1980-1987 nos grupos etários de < 15 anos e 50 anos e mais e para formas paucibacilares; (ii) 1988-1995 para as faixas de 15-19 anos, 20-29 e 50 anos e mais e para formas multibacilares; (iii) 1996-2003 no grupo de 20-29 anos e formas paucibacilares. Os indicadores de avaliação da endemia apontaram patamares estáveis do grau de incapacidade 2 (em média 6%); a proporção de casos entre < 15 anos situou-se abaixo de 10% e a de abandono de tratamento em torno de 6%. A prevalência apresentou forte declínio. A tendência crescente pode ser explicada, em parte pela maior sensibilidade da vigilância, mas a elevada proporção entre < 15 anos aponta a necessidade de estudos visando ao melhor conhecimento dos resíduos de fontes de infecção especialmente no domicílio.

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P>Antibody-mediated rejection (AMR) requires specific diagnostic tools and treatment and is associated with lower graft survival. We prospectively screened C4d in pancreas (n = 35, in 27 patients) and kidney (n = 33, in 21 patients) for cause biopsies. Serum amylase and lipase, amylasuria, fasting blood glucose (FBG) and 2-h capillary glucose (CG) were also analysed. We found that 27.3% of kidney biopsies and 43% of pancreatic biopsies showed C4d staining (66.7% and 53.3% diffuse in peritubular and interacinar capillaries respectively). Isolated exocrine dysfunction was the main indication for pancreas biopsy (54.3%) and was followed by both exocrine and endocrine dysfunctions (37.1%) and isolated endocrine dysfunction (8.6%). Laboratorial parameters were comparable between T-cell mediated rejection and AMR: amylase 151.5 vs. 149 U/l (P = 0.075), lipase 1120 vs. 1288.5 U/l (P = 0.83), amylasuria variation 46.5 vs. 61% (P = 0.97), FBG 69 vs. 97 mg/dl (P = 0.20) and 2-h CG maximum 149.5 vs. 197.5 mg/dl (P = 0.49) respectively. Amylasuria values after treatment correlated with pancreas allograft loss (P = 0.015). These data suggest that C4d staining should be routinely investigated when pancreas allograft dysfunction is present because of its high detection rate in cases of rejection.

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Objective. The purpose of this study was to estimate the Down syndrome detection and false-positive rates for second-trimester sonographic prenasal thickness (PT) measurement alone and in combination with other markers. Methods. Multivariate log Gaussian modeling was performed using numerical integration. Parameters for the PT distribution, in multiples of the normal gestation-specific median (MoM), were derived from 105 Down syndrome and 1385 unaffected pregnancies scanned at 14 to 27 weeks. The data included a new series of 25 cases and 535 controls combined with 4 previously published series. The means were estimated by the median and the SDs by the 10th to 90th range divided by 2.563. Parameters for other markers were obtained from the literature. Results. A log Gaussian model fitted the distribution of PT values well in Down syndrome and unaffected pregnancies. The distribution parameters were as follows: Down syndrome, mean, 1.334 MoM; log(10) SD, 0.0772; unaffected pregnancies, 0.995 and 0.0752, respectively. The model-predicted detection rates for 1%, 3%, and 5% false-positive rates for PT alone were 35%, 51%, and 60%, respectively. The addition of PT to a 4 serum marker protocol increased detection by 14% to 18% compared with serum alone. The simultaneous sonographic measurement of PT and nasal bone length increased detection by 19% to 26%, and with a third sonographic marker, nuchal skin fold, performance was comparable with first-trimester protocols. Conclusions. Second-trimester screening with sonographic PT and serum markers is predicted to have a high detection rate, and further sonographic markers could perform comparably with first-trimester screening protocols.

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OBJECTIVES To evaluate the initial results of a prostate cancer screening program using mobile units in Brazil. METHODS Since 2004, we have conducted a program of prostate cancer screening using mobile units across 231 municipalities from 6 Brazilian states. RESULTS A total of 17 571 men were evaluated by clinical history, digital rectal examination (DRE), and serum free and total prostate-specific antigen (PSA) levels. The recommendations for biopsy were a PSA level of >= 4.0 ng/mL, DRE findings suspicious for cancer, or a PSA level of 2.5-4.0 ng/mL with a percent-free PSA level <15%. The biopsy protocol included 12 biopsy cores from the peripheral zone, 2 from the transition zone, and additional sampling of suspicious areas. The cumulative cancer detection rate was 3.7%. The main indication for biopsy was a PSA level of >= 4.0 ng/mL (51.2%), with a positive predictive value (PPV) of 44.1%. Another 19.7% of biopsied men had suspicious DRE findings with a normal PSA level (PPV 23.5%). A percent-free PSA level of <15% in men with a PSA level of 2.5-4.0 ng/mL and normal DRE findings yielded a PPV of 31.1%. The PPV was greater (70.9%) for the 7.1% of men with both suspicious DRE findings and a PSA level of >4.0 ng/mL. Most cancers were Stage T1-T2 (93.4%), and the percentage of Gleason score of >= 7 was 32.5%. The proportion of insignificant cancers according to Epstein`s criteria was 13.5%. CONCLUSIONS A mobile prostate cancer screening unit enabled an underserved population to gain access to specialized care through the public healthcare system. The cancer detection rate in this population was similar to those from international studies. UROLOGY 76: 1052-1057, 2010. (C) 2010 Published by Elsevier Inc.

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Group C rotavirus (GpCRV) has a worldwide distribution; however, its epidemiology and ecology are still unclear. Evidence for a possible zoonotic role has been postulated recently for Brazilian children strains. The aim of this study was to monitor GpCRV in children <= 15 years with acute gastroenteritis during the 2007-2010 national Brazilian rotavirus surveillance, and to undertake the molecular characterization of the major VP6 capsid protein. A total of 3,019 fecal samples were first screened for Group A rotavirus (GpARV). A total of 2,205 GpARV ELISA negative samples were tested further for the presence of GpCRV by SDS-PAGE, electronic microscopy, and RT-PCR for the VP6 gene. The genetic diversity of GpCRV was carried out by sequencing the VP6 gene. GpARV and GpCRV infections were detected in 24.6% (742/3,019) and 0.3% (8/3,019), respectively. The GpCRV detection rate increased from 0.2% (1/422) in 2007 to 1% (7/708) in 2008, and GpCRV cases were not detected in 2009 and 2010. The phylogenetic analysis indicated that the strains belonged to the human lineage, and showed a genetic relationship with the GpCRV strain from Japan isolated in 2009. None of the study sequences was related closely to animal GpCRV strains. This study provides further evidence that GpCRV is a minor cause of acute childhood gastroenteritis in Brazil, and does not suggest that GpCRV may assume epidemiological importance in the future, even after the introduction of a GpARV vaccine. In addition, the molecular analyses of the GpCRV samples in this study do not support the zoonotic hypothesis. J. Med. Virol. 83: 1631-1636, 2011. (C) 2011 Wiley-Liss, Inc.

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Conventional karyotyping detects anomalies in 3-15% of patients with multiple congenital anomalies and mental retardation (MCA/MR). Whole-genome array screening (WGAS) has been consistently suggested as the first choice diagnostic test for this group of patients, but it is very costly for large-scale use in developing countries. We evaluated the use of a combination of Multiplex Ligation-dependent Probe Amplification (MLPA) kits to increase the detection rate of chromosomal abnormalities in MCA/MR patients. We screened 261 MCA/MR patients with two subtelomeric and one microdeletion kits. This would theoretically detect up to 70% of all submicroscopic abnormalities. Additionally we scored the de Vries score for 209 patients in an effort to find a suitable cut-off for MLPA screening. Our results reveal that chromosomal abnormalities were present in 87 (33.3%) patients, but only 57 (21.8%) were considered causative. Karyotyping detected 15 abnormalities (6.9%), while MLPA identified 54 (20.7%). Our combined MLPA screening raised the total detection number of pathogenic imbalances more than three times when compared to conventional karyotyping. We also show that using the de Vries score as a cutoff for this screening would only be suitable under financial restrictions. A decision analytic model was constructed with three possible strategies: karyotype, karyotype + MLPA and karyotype + WGAS. Karyotype + MLPA strategy detected anomalies in 19.8% of cases which account for 76.45% of the expected yield for karyotype + WGAS. Incremental Cost Effectiveness Ratio (ICER) of MLPA is three times lower than that of WGAS, which means that, for the same costs, we have three additional diagnoses with MLPA but only one with WGAS. We list all causative alterations found, including rare findings, such as reciprocal duplications of regions deleted in Sotos and Williams-Beuren syndromes. We also describe imbalances that were considered polymorphisms or rare variants, such as the new SNP that confounded the analysis of the 22q13.3 deletion syndrome. (C) 2011 Elsevier Masson SAS. All rights reserved.

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Objectives To assess the detection rate of congenital fetal malformations and specific problems related to routine ultrasound screening in women with pre-existing diabetes. Methods A retrospective study was carried out to assess the performance of routine ultrasound screening in women with pre-existing diabetes (Types 1 and 2) within a tertiary institution. The incidence, type and risk factors for congenital fetal malformations were determined. The detection rate of fetal anomalies for diabetic women was compared with that for the low-risk population. Factors affecting these detection rates were evaluated. Results During the study period, 12 169 low-risk pregnant women and 130 women with pre-existing diabetes had routine ultrasound screening performed within the institution. A total of 10 major anomalies (7.7%) and three minor anomalies (2.3%) were present in the fetuses of the diabetic women. Central nervous system and cardiovascular system anomalies accounted for 60% of the major anomalies. Peri-conceptional hemoglobin A 1 c of more than 9% was associated with a high prevalence of major anomalies (14311000). Women who had fetuses with major anomalies bad a significantly higher incidence of obesity (78% vs. 37%; P < 0.05). Ultrasound examination of these diabetic pregnancies showed high incidences of suboptimal image quality (37%), incomplete examinations, and repeat examinations (17%). Compared to the 'low-risk' non-diabetic population from the same institution, the relative risk for a major congenital anomaly among the diabetic women was 5.9-fold higher (95% confidence interval, 2.9-11.9). The detection rate for major fetal anomalies was significantly lower for diabetic women (30% vs. 73%; P < 0.01), and the mean body mass index for the diabetic group was significantly higher (29 vs. 23 kg/m(2); P < 0.001). Conclusion The incidence of congenital anomalies is higher in diabetic pregnancies. Unfortunately, the detection rate for fetal anomalies by antenatal ultrasound scan was significantly, worse than that for the low-risk population. This is likely to be related to the maternal body habitus and unsatisfactory examinations. Methods to overcome these difficulties are discussed.