The Experts below are selected from a list of 168 Experts worldwide ranked by ideXlab platform
Jim Austin - One of the best experts on this subject based on the ideXlab platform.
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A Survey of Outlier Detection Methodoligies
Artificial Intelligence Review, 2004Co-Authors: Victoria J. Hodge, Jim AustinAbstract:Outlier detection has been used for centuries to detect and, where appropriate, remove anomalous observations from data. Outliers arise due to mechanical faults, changes in system behaviour, fraudulent behaviour, human Error, Instrument Error or simply through natural deviations in populations. Their detection can identify system faults and fraud before they escalate with potentially catastrophic consequences. It can identify Errors and remove their contaminating effect on the data set and as such to purify the data for processing. The original outlier detection methods were arbitrary but now, principled and systematic techniques are used, drawn from the full gamut of Computer Science and Statistics. In this paper, we introduce a survey of contemporary techniques for outlier detection. We identify their respective motivations and distinguish their advantages and disadvantages in a comparative review.
Tandakha Ndiaye Dieye - One of the best experts on this subject based on the ideXlab platform.
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multisite evaluation of a point of care Instrument for cd4 t cell enumeration using venous and finger prick blood the pima cd4
Journal of Acquired Immune Deficiency Syndromes, 2011Co-Authors: Papa Alassane Diaw, Ga Raldine Daneau, Abdoul Aziz Coly, B Ndiaye, Djibril Wade, Makhtar Camara, Souleymane Mboup, Luc Kestens, Tandakha Ndiaye DieyeAbstract:BACKGROUND: CD4(+) T-cell enumeration (CD4 count) is used as a criterion to initiate antiretroviral therapy (ART) in HIV patients and to monitor treatment efficacy. However, simple, affordable, and reliable point-of-care (POC) Instruments adapted to resource-limited settings are still lacking. The PIMA CD4 analyzer is a new POC Instrument for CD4 counting that uses disposable cartridges and a battery-powered analyzer. METHODS: Whole blood samples were taken by venipuncture or by finger prick from 300 subjects, including HIV-infected patients and HIV (-) controls. CD4 counts were measured by PIMA (using venous or capillary blood) and by FACSCount (using venous blood) considered as the reference. RESULTS: Similar CD4 counts were obtained by PIMA and FACSCount using either HIV+ venous blood or HIV+ finger-prick blood samples. However, with a concordance coefficient of 0.88 and a Pearson correlation of 0.89, finger-prick blood performed not as good as venous blood (0.97 and 0.98, respectively). For a clinical decision to start ART at 200 CD4 cells per microliter, sensitivity of PIMA was 90%/91% and specificity 98%/96% for venous/finger-prick blood, respectively, and for a treatment threshold of 350 CD4 cells per microliter, the sensitivity was 98%/91% and the specificity was 79%/80% for venous/finger-prick blood, respectively. Repeatability (precision) on venous blood resulted in a coefficient of variation of 4%. Using finger-prick blood, the average Instrument Error frequency resulting in aborted analyses was 14%. CONCLUSIONS: PIMA is a good POC Instrument for screening adult HIV-infected patients in resource-limited settings for treatment eligibility. Its performance on finger-prick blood is not as good as on venous blood. Adequate training for correct use of finger-prick blood samples is mandatory.
Victoria J. Hodge - One of the best experts on this subject based on the ideXlab platform.
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A Survey of Outlier Detection Methodoligies
Artificial Intelligence Review, 2004Co-Authors: Victoria J. Hodge, Jim AustinAbstract:Outlier detection has been used for centuries to detect and, where appropriate, remove anomalous observations from data. Outliers arise due to mechanical faults, changes in system behaviour, fraudulent behaviour, human Error, Instrument Error or simply through natural deviations in populations. Their detection can identify system faults and fraud before they escalate with potentially catastrophic consequences. It can identify Errors and remove their contaminating effect on the data set and as such to purify the data for processing. The original outlier detection methods were arbitrary but now, principled and systematic techniques are used, drawn from the full gamut of Computer Science and Statistics. In this paper, we introduce a survey of contemporary techniques for outlier detection. We identify their respective motivations and distinguish their advantages and disadvantages in a comparative review.
Papa Alassane Diaw - One of the best experts on this subject based on the ideXlab platform.
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multisite evaluation of a point of care Instrument for cd4 t cell enumeration using venous and finger prick blood the pima cd4
Journal of Acquired Immune Deficiency Syndromes, 2011Co-Authors: Papa Alassane Diaw, Ga Raldine Daneau, Abdoul Aziz Coly, B Ndiaye, Djibril Wade, Makhtar Camara, Souleymane Mboup, Luc Kestens, Tandakha Ndiaye DieyeAbstract:BACKGROUND: CD4(+) T-cell enumeration (CD4 count) is used as a criterion to initiate antiretroviral therapy (ART) in HIV patients and to monitor treatment efficacy. However, simple, affordable, and reliable point-of-care (POC) Instruments adapted to resource-limited settings are still lacking. The PIMA CD4 analyzer is a new POC Instrument for CD4 counting that uses disposable cartridges and a battery-powered analyzer. METHODS: Whole blood samples were taken by venipuncture or by finger prick from 300 subjects, including HIV-infected patients and HIV (-) controls. CD4 counts were measured by PIMA (using venous or capillary blood) and by FACSCount (using venous blood) considered as the reference. RESULTS: Similar CD4 counts were obtained by PIMA and FACSCount using either HIV+ venous blood or HIV+ finger-prick blood samples. However, with a concordance coefficient of 0.88 and a Pearson correlation of 0.89, finger-prick blood performed not as good as venous blood (0.97 and 0.98, respectively). For a clinical decision to start ART at 200 CD4 cells per microliter, sensitivity of PIMA was 90%/91% and specificity 98%/96% for venous/finger-prick blood, respectively, and for a treatment threshold of 350 CD4 cells per microliter, the sensitivity was 98%/91% and the specificity was 79%/80% for venous/finger-prick blood, respectively. Repeatability (precision) on venous blood resulted in a coefficient of variation of 4%. Using finger-prick blood, the average Instrument Error frequency resulting in aborted analyses was 14%. CONCLUSIONS: PIMA is a good POC Instrument for screening adult HIV-infected patients in resource-limited settings for treatment eligibility. Its performance on finger-prick blood is not as good as on venous blood. Adequate training for correct use of finger-prick blood samples is mandatory.
T J Jackson - One of the best experts on this subject based on the ideXlab platform.
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an observing system simulation experiment for hydros radiometer only soil moisture products
IEEE Transactions on Geoscience and Remote Sensing, 2005Co-Authors: Wade T Crow, S Chan, Dara Entekhabi, Paul R Houser, T J Jackson, E G Njoku, P E Oneill, Xiwu ZhanAbstract:Based on 1-km land surface model geophysical predictions within the United States Southern Great Plains (Red-Arkansas River basin), an observing system simulation experiment (OSSE) is carried out to assess the impact of land surface heterogeneity, Instrument Error, and parameter uncertainty on soil moisture products derived from the National Aeronautics and Space Administration Hydrosphere State (Hydros) mission. Simulated retrieved soil moisture products are created using three distinct retrieval algorithms based on the characteristics of passive microwave measurements expected from Hydros. The accuracy of retrieval products is evaluated through comparisons with benchmark soil moisture fields obtained from direct aggregation of the original simulated soil moisture fields. The analysis provides a quantitative description of how land surface heterogeneity, Instrument Error, and inversion parameter uncertainty impacts propagate through the measurement and retrieval process to degrade the accuracy of Hydros soil moisture products. Results demonstrate that the discrete set of Error sources captured by the OSSE induce root mean squared Errors of between 2.0% and 4.5% volumetric in soil moisture retrievals within the basin. Algorithm robustness is also evaluated for the case of artificially enhanced vegetation water content (W) values within the basin. For large W(>3 kg/spl middot/m/sup -2/), a distinct positive bias, attributable to the impact of sub- footprint-scale landcover heterogeneity, is identified in soil moisture retrievals. Prospects for the removal of this bias via a correction strategy for inland water and/or the implementation of an alternative aggregation strategy for surface vegetation and roughness parameters are discussed.
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soil moisture mapping at regional scales using microwave radiometry the southern great plains hydrology experiment
IEEE Transactions on Geoscience and Remote Sensing, 1999Co-Authors: T J Jackson, D Le M Vine, A Oldak, P Starks, C T Swift, J Isham, M HakenAbstract:Surface soil moisture retrieval algorithms based on passive microwave observations, developed and verified at high spatial resolution, were evaluated in a regional scale experiment. Using previous investigations as a base, the Southern Great Plains Hydrology Experiment (SGP97) was designed and conducted to extend the algorithm to coarser resolutions, larger regions with more diverse conditions, and longer time periods. The L-band electronically scanned thinned array radiometer (ESTAR) was used for daily mapping of surface soil moisture over an area greater than 10000 km/sup 2/ for a one month period. Results show that the soil moisture retrieval algorithm performed the same as in previous investigations, demonstrating consistency of both the retrieval and the Instrument. Error levels were on the order of 3% for area Integrated averages of sites used for validation. This result showed that for the coarser resolution used that the theory and techniques employed in the algorithm apply at this scale. Spatial patterns observed in the Little Washita Watershed in previous investigations were also observed. These results showed that soil texture dominated the spatial pattern at this scale. However, the regional soil moisture patterns were a reflection of the spatially variable rainfall and soil texture patterns were not as obvious.