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Fulltext Artificial neural network with Taguchi method for robust classification model to improve classification accuracy of breast cancer

Rahman MA, Muniyandi RC, Albashish D, Rahman MM, Usman OL

PeerJ Comput Sci, 2021;7:e344.
PMID: 33816995 DOI: 10.7717/peerj-cs.344

Artificial neural networks (ANN) perform well in real-world classification problems. In this paper, a robust classification model using ANN was constructed to enhance the accuracy of breast cancer classification. The Taguchi method was used to determine the suitable number of neurons in a single hidden layer of the ANN. The selection of a suitable number of neurons helps to solve the overfitting problem by affecting the classification performance of an ANN. With this, a robust classification model was then built for breast cancer classification. Based on the Taguchi method results, the suitable number of neurons selected for the hidden layer in this study is 15, which was used for the training of the proposed ANN model. The developed model was benchmarked upon the Wisconsin Diagnostic Breast Cancer Dataset, popularly known as the UCI dataset. Finally, the proposed model was compared with seven other existing classification models, and it was confirmed that the model in this study had the best accuracy at breast cancer classification, at 98.8%. This confirmed that the proposed model significantly improved performance.

Matched MeSH terms: Wisconsin
Evaluating the Performance of a Relative Humidity-Based Warning System for Sooty Blotch and Flyspeck in Iowa

Rosli H, Mayfield DA, Batzer JC, Dixon PM, Zhang W, Gleason ML

Plant Dis, 2017 Oct;101(10):1721-1728.
PMID: 30676929 DOI: 10.1094/PDIS-02-17-0294-RE

A warning system for the sooty blotch and flyspeck (SBFS) fungal disease complex of apple, developed originally for use in the southeastern United States, was modified to provide more reliable assessment of SBFS risk in Iowa. Modeling results based on previous research in Iowa and Wisconsin had suggested replacing leaf wetness duration with cumulative hours of relative humidity (RH) ≥97% as the weather input to the SBFS warning system. The purpose of the present study was to evaluate the performance of a RH-based SBFS warning system, and to assess the potential economic benefits for its use in Iowa. The warning system was evaluated in two separate sets of trials-trial 1 during 2010 and 2011, and trial 2 during 2013-2015-using action thresholds based on cumulative hours of RH ≥97% and ≥90%, respectively, in conjunction with two different fungicide regimes. The warning system was compared with a traditional calendar-based system that specified spraying at predetermined intervals of 10 to 14 days. In trial 1, use of the RH ≥97% threshold caused substantial differences between two RH sensors in recording number of hours exceeding the threshold. When both RH thresholds were compared for 2013-2015, on average, RH ≥90% resulted in a 53% reduction in variation of cumulative hours between two identical RH sensors placed adjacent to each other in an apple tree canopy. Although both the SBFS warning system and the calendar-based system resulted in equivalent control of SBFS, the warning system required fewer fungicide sprays than the calendar-based system, with an average of 3.8 sprays per season (min = 2; max = 5) vs. 6.4 sprays per season (min = 5; max = 8), respectively. The two fungicide regimes provided equivalent SBFS control when used in conjunction with the warning system. A partial budget analysis showed that using the SBFS warning system with a threshold of RH ≥90% was cost effective for orchard sizes of >1 ha. The revised warning system has potential to become a valuable decision support tool for Midwest apple growers because it reduces fungicide costs while protecting apples as effectively as a calendar-based spray schedule. The next step toward implementation of the SBFS warning system in the North Central U.S. should be multiyear field testing in commercial orchards throughout the region.

Matched MeSH terms: Wisconsin
Fulltext The epiphytic microbiota of the globally widespread macroalga Cladophora glomerata (Chlorophyta, Cladophorales)

Zulkifly S, Hanshew A, Young EB, Lee P, Graham ME, Graham ME, et al.

Am J Bot, 2012 Sep;99(9):1541-52.
PMID: 22947483 DOI: 10.3732/ajb.1200161

The filamentous chlorophyte Cladophora produces abundant nearshore populations in marine and freshwaters worldwide, often dominating periphyton communities and producing nuisance growths under eutrophic conditions. High surface area and environmental persistence foster such high functional and taxonomic diversity of epiphytic microfauna and microalgae that Cladophora has been labeled an ecological engineer. We tested the hypotheses that (1) Cladophora supports a structurally and functionally diverse epiphytic prokaryotic microbiota that influences materials cycling and (2) mutualistic host-microbe interactions occur. Because previous molecular sequencing-based analyses of the microbiota of C. glomerata found as western Lake Michigan beach drift had identified pathogenic associates such as Escherichia coli, we also asked if actively growing lentic C. glomerata harbors known pathogens.

Matched MeSH terms: Wisconsin
Fulltext Measles among U.S.-bound refugees from Malaysia--California, Maryland, North Carolina, and Wisconsin, August-September 2011

Centers for Disease Control and Prevention (CDC)

MMWR Morb Mortal Wkly Rep, 2011 Sep 23;60(37):1281-2.
PMID: 21937975

On August 26, 2011, California public health officials notified CDC of a suspected measles case in an unvaccinated male refugee aged 15 years from Burma (the index patient), who had lived in an urban area of Kuala Lumpur, Malaysia, which is experiencing ongoing measles outbreaks. Currently, approximately 92,000 such refugees are living in urban communities in Malaysia. Resettlement programs in the United States and other countries are ongoing. The health and vaccination status of urban refugees are largely unknown.

Matched MeSH terms: Wisconsin
Fulltext Association of Environmental Uncertainty With Altered Decision-making and Learning Mechanisms in Youths With Obsessive-Compulsive Disorder

Marzuki AA, Tomic I, Ip SHY, Gottwald J, Kanen JW, Kaser M, et al.

JAMA Netw Open, 2021 Nov 01;4(11):e2136195.
PMID: 34842925 DOI: 10.1001/jamanetworkopen.2021.36195

IMPORTANCE: Adults with obsessive-compulsive disorder (OCD) display perseverative behavior in stable environments but exhibit vacillating choice when payoffs are uncertain. These findings may be associated with intolerance of uncertainty and compulsive behaviors; however, little is known about the mechanisms underlying learning and decision-making in youths with OCD because research into this population has been limited.
OBJECTIVE: To investigate cognitive mechanisms associated with decision-making in youths with OCD by using executive functioning tasks and computational modeling.
DESIGN, SETTING, AND PARTICIPANTS: In this cross-sectional study, 50 youths with OCD (patients) and 53 healthy participants (controls) completed a probabilistic reversal learning (PRL) task between January 2014 and March 2020. A separate sample of 27 patients and 46 controls completed the Wisconsin Card Sorting Task (WCST) between January 2018 and November 2020. The study took place at the University of Cambridge in the UK.
MAIN OUTCOMES AND MEASURES: Decision-making mechanisms were studied by fitting hierarchical bayesian reinforcement learning models to the 2 data sets and comparing model parameters between participant groups. Model parameters included reward and punishment learning rates (feedback sensitivity), reinforcement sensitivity and decision consistency (exploitation), and stickiness (perseveration). Associations of receipt of serotonergic medication with performance were assessed.
RESULTS: In total, 50 patients (29 female patients [58%]; median age, 16.6 years [IQR, 15.3-18.0 years]) and 53 controls (30 female participants [57%]; median age, 16.4 years [IQR, 14.8-18.0 years]) completed the PRL task. A total of 27 patients (18 female patients [67%]; median age, 16.1 years [IQR, 15.2-17.2 years]) and 46 controls (28 female participants [61%]; median age, 17.2 [IQR, 16.3-17.6 years]) completed the WCST. During the reversal phase of the PRL task, patients made fewer correct responses (mean [SD] proportion: 0.83 [0.16] for controls and 0.61 [0.31] for patients; 95% CI, -1.31 to -0.64) and switched choices more often following false-negative feedback (mean [SD] proportion: 0.09 [0.16] for controls vs 0.27 [0.34] for patients; 95% CI, 0.60-1.26) and true-positive feedback (mean [SD] proportion: 0.93 [0.17] for controls vs 0.73 [0.34] for patients; 95% CI, -2.17 to -1.31). Computational modeling revealed that patients displayed enhanced reward learning rates (mean difference [MD], 0.21; 95% highest density interval [HDI], 0.04-0.38) but decreased punishment learning rates (MD, -0.29; 95% HDI, -0.39 to -0.18), reinforcement sensitivity (MD, -4.91; 95% HDI, -9.38 to -1.12), and stickiness (MD, -0.35; 95% HDI, -0.57 to -0.11) compared with controls. There were no group differences on standard WCST measures and computational model parameters. However, patients who received serotonergic medication showed slower response times (mean [SD], 1420.49 [279.71] milliseconds for controls, 1471.42 [212.81] milliseconds for patients who were unmedicated, and 1738.25 [349.23] milliseconds for patients who were medicated) (control vs medicated MD, -320.26 [95% CI, -547.00 to -88.68]) and increased unique errors (mean [SD] proportion: 0.001 [0.004] for controls, 0.002 [0.004] for patients who were unmedicated, and 0.008 [0.01] for patients who were medicated) (control vs medicated MD, -0.007 [95% CI, -3.14 to -0.36]) on the WCST.
CONCLUSIONS AND RELEVANCE: The results of this cross-sectional study indicated that youths with OCD showed atypical probabilistic reversal learning but were generally unimpaired on the deterministic WCST, although unexpected results were observed for patients receiving serotonergic medication. These findings have implications for reframing the understanding of early-onset OCD as a disorder in which decision-making is associated with uncertainty in the environment, a potential target for therapeutic treatment. These results provide continuity with findings in adults with OCD.

Matched MeSH terms: Wisconsin