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Träfflista för sökning "WFRF:(Ng Bernard) "

Sökning: WFRF:(Ng Bernard)

  • Resultat 1-10 av 13
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1.
  • Romagnoni, Alberto, et al. (författare)
  • Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data
  • 2019
  • Ingår i: Scientific reports. - 2045-2322. ; 9:1, s. 10351
  • Tidskriftsartikel (refereegranskat)abstract
    • Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers.
2.
  • de Jong, Simone, et al. (författare)
  • Applying polygenic risk scoring for psychiatric disorders to a large family with bipolar disorder and major depressive disorder
  • 2018
  • Ingår i: Communications Biology. - Nature Publishing Group. - 2399-3642. ; 1
  • Tidskriftsartikel (refereegranskat)abstract
    • Psychiatric disorders are thought to have a complex genetic pathology consisting of interplay of common and rare variation. Traditionally, pedigrees are used to shed light on the latter only, while here we discuss the application of polygenic risk scores to also highlight patterns of common genetic risk. We analyze polygenic risk scores for psychiatric disorders in a large pedigree (n ~ 260) in which 30% of family members suffer from major depressive disorder or bipolar disorder. Studying patterns of assortative mating and anticipation, it appears increased polygenic risk is contributed by affected individuals who married into the family, resulting in an increasing genetic risk over generations. This may explain the observation of anticipation in mood disorders, whereby onset is earlier and the severity increases over the generations of a family. Joint analyses of rare and common variation may be a powerful way to understand the familial genetics of psychiatric disorders.
3.
  • Evangelou, Evangelos, et al. (författare)
  • Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits.
  • 2018
  • Ingår i: Nature Genetics. - 1061-4036 .- 1546-1718. ; 50:10, s. 1412-1425
  • Tidskriftsartikel (refereegranskat)abstract
    • High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.
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4.
  • Gandhi, Kanika, et al. (författare)
  • Towards data mining based decision support in manufacturing maintenance
  • 2018
  • Ingår i: Procedia CIRP. - Elsevier. - 2212-8271. ; 72, s. 261-265
  • Tidskriftsartikel (refereegranskat)abstract
    • The current work presents a decision support system architecture for evaluating the features representing the health status to predict maintenance actions and remaning useful life of component. The evaluation is possible through pattern analysis of past and current measurements of the focused research components. Data mining visualization tools help in creating the most suitable patterns and learning insights from them. Estimations like features split values or measurement frequency of the component is achieved through classification methods in data mining. This paper presents how the quantitative results generated from data mining can be used to support decision making of domain experts.
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8.
  • Jin, Taiyi, et al. (författare)
  • Environmental epidemiological study and estimation of benchmark dose for renal dysfunction in a cadmium-polluted area in China.
  • 2004
  • Ingår i: Biometals : an international journal on the role of metal ions in biology, biochemistry, and medicine. - 0966-0844. ; 17:5, s. 525-30
  • Tidskriftsartikel (refereegranskat)abstract
    • We have performed a study aimed at investigating the critical concentration of urinary cadmium (UCd) required for the development of renal dysfunction. We studied population groups (totally 790 persons) living in two cadmium exposed areas and one control area in China. UCd, was determined as an indicator of cadmium exposure and accumulation, while the concentrations of N-acetyl-beta-D-glucosaminidase (NAG), its iso-form B (NAG-B), beta2-microglobulin (B2M), retinol binding protein (RBP), and albumin (ALB) in urine were measured as indicators of the renal effects caused by cadmium. There was a significantly increased prevalence of hyperNAGuria, hyperNAG-Buria, hyperB2Muria, hyperRBPuria and hyperALBuria with increasing levels of Cd excretion in urine. We used the benchmark dose (BMD) procedure to estimate the critical concentration of urinary cadmium in this general population. The lower confidence limit of the BMD (LBMD-05) of urinary cadmium for a 5% level of risk above the background level was estimated for each of the renal effect indicators. The BMD-05/LBMD-05 were estimated to be 4.46/3.99, 6.70/5.87, 8.36/7.31, 7.98/6.98 and 15.06/12.18 microg/g creatinine for urinary NAG-B, NAG, B2M, RBP and ALB, respectively. Our findings suggest, based on the present study, that the Lower Confidence Limit of the Population Critical Concentration of UCd (LPCCUCd-05) of tubular dysfunction for 5% excess risk level above the background may be ca. 3-4 microg/g creatinine, and that cadmium concentration in urine should be kept below this level to prevent renal tubular damage. This report is the first to use the BMD method in this field and to define the concept of critical concentration in urine.
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9.
  • Schmidt, Bernard, 1981-, et al. (författare)
  • Integration of events and offline measurement data from a population of similar entities for condition monitoring
  • ????
  • Ingår i: International journal of computer integrated manufacturing (Print). - 0951-192X.
  • Tidskriftsartikel (refereegranskat)abstract
    • In this paper, an approach for integration of data from different sources and from a population of similar monitored entities is presented with evaluation procedure based on multiple machine learning methods that allows selection of a proper combination of methods for data integration and feature selection. It is exemplified on the real-world case from manufacturing industry with application to double ball-bar measurement from a population of machine tools. Historical data from the period of four years from a population of 29 similar multitask machine tools are analysed. Several feature selection methods are evaluated. Finally, simple economic evaluation is presented with application to proposed condition based approach. With assumed parameters, potential improvement in long term of 6 times reduced amount of unplanned stops and 40% reduced cost has been indicated with respect to optimal time based replacement policy.
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