Performing Feature Selection with ACO

R. Jensen, 'Performing Feature Selection with ACO. Swarm Intelligence and Data Mining,' A. Abraham, C. Grosan and V. Ramos (eds.), Studies in Computational Intelligence, vol. 34, pp. 45-73. 2006.

Tolerance-based and Fuzzy-Rough Feature Selection.

R. Jensen and Q. Shen, 'Tolerance-based and Fuzzy-Rough Feature Selection,' Proceedings of the 16th International Conference on Fuzzy Systems (FUZZ-IEEE'07), pp. 877-882, 2007.

Webpage Classification with ACO-enhanced Fuzzy-Rough Feature Selection.

R. Jensen and Q. Shen, 'Webpage Classification with ACO-enhanced Fuzzy-Rough Feature Selection,' Proceedings of the Fifth International Conference on Rough Sets and Current Trends in Computing (RSCTC 2006), LNAI 4259, pp. 147-156, 2006.

Aiding classification of gene expression data with feature selection: a comparative study

C. Shang and Q. Shen. Aiding classification of gene expression data with feature selection: a comparative study. Computational Intelligence Research, 1(1):68-76.

Contour Generator Points for Threshold Selection and a Novel Photo-Consistency Measure for Space Carving

Space carving has emerged as a powerful method for multiview scene reconstruction. Although a wide variety of methods have been proposed, the quality of the reconstruction remains highly-dependent on the photometric consistency measure, and the threshold used to carve away voxels. In this paper, we present a novel photo-consistency measure that is motivated by a multiset variant of the chamfer distance. The new measure is robust to high amounts of within-view color variance and also takes into account the projection angles of back-projected pixels. Another critical issue in space carving is the selection of the photo-consistency threshold used to determine what surface voxels are kept or carved away. In this paper, a reliable threshold selection technique is proposed that examines the photo-consistency values at contour generator points. Contour generators are points that lie on both the surface of the object and the visual hull. To determine the threshold, a percentile ranking of the photo-consistency values of these generator points is used. This improved technique is applicable to a wide variety of photo-consistency measures, including the new measure presented in this paper. Also presented in this paper is a method to choose between photo-consistency measures, and voxel array resolutions prior to carving using receiver operating characteristic (ROC) curves.

Bayesian variable selection in structured high-dimensional covariate spaces with applications in genomics

We consider the problem of variable selection in regression modeling in high-dimensional spaces where there is known structure among the covariates. This is an unconventional variable selection problem for two reasons: (1) The dimension of the covariate space is comparable, and often much larger, than the number of subjects in the study, and (2) the covariate space is highly structured, and in some cases it is desirable to incorporate this structural information in to the model building process. We approach this problem through the Bayesian variable selection framework, where we assume that the covariates lie on an undirected graph and formulate an Ising prior on the model space for incorporating structural information. Certain computational and statistical problems arise that are unique to such high-dimensional, structured settings, the most interesting being the phenomenon of phase transitions. We propose theoretical and computational schemes to mitigate these problems. We illustrate our methods on two different graph structures: the linear chain and the regular graph of degree k. Finally, we use our methods to study a specific application in genomics: the modeling of transcription factor binding sites in DNA sequences. © 2010 American Statistical Association.

Development of a decision aid to inform patients' and families' renal replacement therapy selection decisions.

BACKGROUND: Few educational resources have been developed to inform patients' renal replacement therapy (RRT) selection decisions. Patients progressing toward end stage renal disease (ESRD) must decide among multiple treatment options with varying characteristics. Complex information about treatments must be adequately conveyed to patients with different educational backgrounds and informational needs. Decisions about treatment options also require family input, as families often participate in patients' treatment and support patients' decisions. We describe the development, design, and preliminary evaluation of an informational, evidence-based, and patient-and family-centered decision aid for patients with ESRD and varying levels of health literacy, health numeracy, and cognitive function. METHODS: We designed a decision aid comprising a complementary video and informational handbook. We based our development process on data previously obtained from qualitative focus groups and systematic literature reviews. We simultaneously developed the video and handbook in "stages." For the video, stages included (1) directed interviews with culturally appropriate patients and families and preliminary script development, (2) video production, and (3) screening the video with patients and their families. For the handbook, stages comprised (1) preliminary content design, (2) a mixed-methods pilot study among diverse patients to assess comprehension of handbook material, and (3) screening the handbook with patients and their families. RESULTS: The video and handbook both addressed potential benefits and trade-offs of treatment selections. The 50-minute video consisted of demographically diverse patients and their families describing their positive and negative experiences with selecting a treatment option. The video also incorporated health professionals' testimonials regarding various considerations that might influence patients' and families' treatment selections. The handbook was comprised of written words, pictures of patients and health care providers, and diagrams describing the findings and quality of scientific studies comparing treatments. The handbook text was written at a 4th to 6th grade reading level. Pilot study results demonstrated that a majority of patients could understand information presented in the handbook. Patient and families screening the nearly completed video and handbook reviewed the materials favorably. CONCLUSIONS: This rigorously designed decision aid may help patients and families make informed decisions about their treatment options for RRT that are well aligned with their values.

Selecting renal replacement therapies: what do African American and non-African American patients and their families think others should know? A mixed methods study.

BACKGROUND: Little is known regarding the types of information African American and non-African American patients with chronic kidney disease (CKD) and their families need to inform renal replacement therapy (RRT) decisions. METHODS: In 20 structured group interviews, we elicited views of African American and non-African American patients with CKD and their families about factors that should be addressed in educational materials informing patients' RRT selection decisions. We asked participants to select factors from a list and obtained their open-ended feedback. RESULTS: Ten groups of patients (5 African American, 5 non-African American; total 68 individuals) and ten groups of family members (5 African American, 5 non-African American; total 62 individuals) participated. Patients and families had a range (none to extensive) of experiences with various RRTs. Patients identified morbidity or mortality, autonomy, treatment delivery, and symptoms as important factors to address. Family members identified similar factors but also cited the effects of RRT decisions on patients' psychological well-being and finances. Views of African American and non-African American participants were largely similar. CONCLUSIONS: Educational resources addressing the influence of RRT selection on patients' morbidity and mortality, autonomy, treatment delivery, and symptoms could help patients and their families select RRT options closely aligned with their values. Including information about the influence of RRT selection on patients' personal relationships and finances could enhance resources' cultural relevance for African Americans.

Evaluating marker-guided treatment selection strategies

© 2014, The International Biometric Society.A potential venue to improve healthcare efficiency is to effectively tailor individualized treatment strategies by incorporating patient level predictor information such as environmental exposure, biological, and genetic marker measurements. Many useful statistical methods for deriving individualized treatment rules (ITR) have become available in recent years. Prior to adopting any ITR in clinical practice, it is crucial to evaluate its value in improving patient outcomes. Existing methods for quantifying such values mainly consider either a single marker or semi-parametric methods that are subject to bias under model misspecification. In this article, we consider a general setting with multiple markers and propose a two-step robust method to derive ITRs and evaluate their values. We also propose procedures for comparing different ITRs, which can be used to quantify the incremental value of new markers in improving treatment selection. While working models are used in step I to approximate optimal ITRs, we add a layer of calibration to guard against model misspecification and further assess the value of the ITR non-parametrically, which ensures the validity of the inference. To account for the sampling variability of the estimated rules and their corresponding values, we propose a resampling procedure to provide valid confidence intervals for the value functions as well as for the incremental value of new markers for treatment selection. Our proposals are examined through extensive simulation studies and illustrated with the data from a clinical trial that studies the effects of two drug combinations on HIV-1 infected patients.

Evaluation of the quality of the management of cancer of the corpus uteri-Selection of relevant quality indicators and implementation in Belgium

Objective Describe the methodology and selection of quality indicators (QI) to be implemented in the EFFECT (EFFectiveness of Endometrial Cancer Treatment) project. EFFECT aims to monitor the variability in Quality of Care (QoC) of uterine cancer in Belgium, to compare the effectiveness of different treatment strategies to improve the QoC and to check the internal validity of the QI to validate the impact of process indicators on outcome. Methods A QI list was retrieved from literature, recent guidelines and QI databases. The Belgian Healthcare Knowledge Center methodology was used for the selection process and involved an expert's panel rating the QI on 4 criteria. The resulting scores and further discussion resulted in a final QI list. An online EFFECT module was developed by the Belgian Cancer Registry including the list of variables required for measuring the QI. Three test phases were performed to evaluate the relevance, feasibility and understanding of the variables and to test the compatibility of the dataset. Results 138 QI were considered for further discussion and 82 QI were eligible for rating. Based on the rating scores and consensus among the expert's panel, 41 QI were considered measurable and relevant. Testing of the data collection enabled optimization of the content and the user-friendliness of the dataset and online module. Conclusions This first Belgian initiative for monitoring the QoC of uterine cancer indicates that the previously used QI selection methodology is reproducible for uterine cancer. The QI list could be applied by other research groups for comparison. © 2013 Elsevier Inc.

Gene selection by cooperative competition clustering

Clustering analysis of data from DNA microarray hybridization studies is an essential task for identifying biologically relevant groups of genes. Attribute cluster algorithm (ACA) has provided an attractive way to group and select meaningful genes. However, ACA needs much prior knowledge about the genes to set the number of clusters. In practical applications, if the number of clusters is misspecified, the performance of the ACA will deteriorate rapidly. In fact, it is a very demanding to do that because of our little knowledge. We propose the Cooperative Competition Cluster Algorithm (CCCA) in this paper. In the algorithm, we assume that both cooperation and competition exist simultaneously between clusters in the process of clustering. By using this principle of Cooperative Competition, the number of clusters can be found in the process of clustering. Experimental results on a synthetic and gene expression data are demonstrated. The results show that CCCA can choose the number of clusters automatically and get excellent performance with respect to other competing methods.

Selection of an analytical method for evaluating bovine serum albumin concentrations in pharmaceutical polymeric formulations

Bovine serum albumin (BSA) is a commonly used model protein in the development of pharmaceutical formulations. In order to assay its release from various dosage forms, either the bicinchoninic acid (BCA) assay or a more specific size-exclusion high performance liquid chromatography (SE-HPLC) method are commonly employed. However, these can give erroneous results in the presence of some commonly-used pharmaceutical excipients. We therefore investigated the ability of these methods to accurately determine BSA concentrations in pharmaceutical formulations that also contained various polymers and compared them with a new and compared with a new reverse-phase (RP)–HPLC technique. We found that the RP-HPLC technique was the most suitable method. It gave a linear response in the range of 0.5 -100 µg/ml with a correlation coefficient of 0.9999, a limit of detection of 0.11 µg/ml and quantification of 0.33 µg/ml. The performed ‘t’ test for the estimated and theoretical concentration indicated no significant difference between them providing the accuracy. Low % relative standard deviation values (0.8-1.39%) indicate the precision of the method. Furthermore, the method was used to quantify in vitro BSA release from polymeric freeze-dried formulations.

Enteral feeding methods for nutritional management in patients with head and neck cancers being treated with radiotherapy and/or chemotherapy

Background: This is an update of a Cochrane review first published in The Cochrane Library in Issue 3, 2010.
For many patients with head and neck cancer, oral nutrition will not provide adequate nourishment during treatment with radiotherapy or chemoradiotherapy due to the acute toxicity of treatment, obstruction caused by the tumour, or both. The optimal method of enteral feeding for this patient group has yet to be established.

Objectives: To compare the effectiveness of different enteral feeding methods used in the nutritional management of patients with head and neck cancer receiving radiotherapy or chemoradiotherapy using the clinical outcomes, nutritional status, quality of life and rates of complications.

Search methods: Our extensive search included the Cochrane ENT Group Trials Register, CENTRAL, PubMed, EMBASE, CINAHL, AMED and ISI Web of Science. The date of the most recent search was 13 February 2012.

Selection criteria:Randomised controlled trials comparing one method of enteral feeding with another, e.g. nasogastric (NG) or percutaneous endoscopic gastrostomy (PEG) feeding, for adult patients with a diagnosis of head and neck cancer receiving radiotherapy and/or chemoradiotherapy.

Data collection and analysis:Two authors independently assessed trial quality and extracted data using standardised forms. We contacted study authors for additional information.

Main results: One randomised controlled trial met the criteria for inclusion in this review. No further studies were identified when we updated the searches in 2012.
Patients diagnosed with head and neck cancer, being treated with chemoradiotherapy, were randomised to PEG or NG feeding. In total only 33 patients were eligible for analysis as the trial was terminated early due to poor accrual. A high degree of bias was identified in the study.
Weight loss was greater for the NG group at six weeks post-treatment than for the PEG group (P = 0.001). At six months post-treatment, however, there was no significant difference in weight loss between the two groups. Anthropometric measurements recorded six weeks post-treatment demonstrated lower triceps skin fold thickness for the NG group compared to the PEG group (P = 0.03). No statistically significant difference was found between the two different enteral feeding techniques in relation to complication rates or patient satisfaction. The duration of PEG feeding was significantly longer than for the NG group (P = 0.0006). In addition, the study calculated the cost of PEG feeding to be 10 times greater than that of NG, though this was not found to be significant. There was no difference in the treatment received by the two groups. However, four PEG fed patients and two NG fed patients required unscheduled treatment breaks of a median of two and six days respectively.
We identified no studies of enteral feeding involving any form of radiologically inserted gastrostomy (RIG) feeding or comparing prophylactic PEG versus PEG for inclusion in the review.

Authors' conclusions: There is not sufficient evidence to determine the optimal method of enteral feeding for patients with head and neck cancer receiving radiotherapy and/or chemoradiotherapy. Further trials of the two methods of enteral feeding, incorporating larger sample sizes, are required.

Methodological considerations in reserve system selection: a case study of Malagasy Lemurs.

Although data quality and weighting decisions impact the outputs of reserve selection algorithms, these factors have not been closely studied. We examine these methodological issues in the use of reserve selection algorithms by comparing: (1) quality of input data and (2) use of different weighting methods for prioritizing among species. In 2003, the government of Madagascar, a global biodiversity hotspot, committed to tripling the size of its protected area network to protect 10% of the country’s total land area. We apply the Zonation reserve selection algorithm to distribution data for 52 lemur species to identify priority areas for the expansion of Madagascar’s reserve network. We assess the similarity of the areas selected, as well as the proportions of lemur ranges protected in the resulting areas when different forms of input data were used: extent of occurrence versus refined extent of occurrence. Low overlap between the areas selected suggests that refined extent of occurrence data are highly desirable, and to best protect lemur species, we recommend refining extent of occurrence ranges using habitat and altitude limitations. Reserve areas were also selected for protection based on three different species weighting schemes, resulting in marked variation in proportional representation of species among the IUCN Red List of Threatened Species extinction risk categories. This result demonstrates that assignment of species weights influences whether a reserve network prioritizes maximizing overall species protection or maximizing protection of the most threatened species.

Robust face recognition with partial occlusion, illumination variation and limited training data by optimal feature selection

This study investigates face recognition with partial occlusion, illumination variation and their combination, assuming no prior information about the mismatch, and limited training data for each person. The authors extend their previous posterior union model (PUM) to give a new method capable of dealing with all these problems. PUM is an approach for selecting the optimal local image features for recognition to improve robustness to partial occlusion. The extension is in two stages. First, authors extend PUM from a probability-based formulation to a similarity-based formulation, so that it operates with as little as one single training sample to offer robustness to partial occlusion. Second, they extend this new formulation to make it robust to illumination variation, and to combined illumination variation and partial occlusion, by a novel combination of multicondition relighting and optimal feature selection. To evaluate the new methods, a number of databases with various simulated and realistic occlusion/illumination mismatches have been used. The results have demonstrated the improved robustness of the new methods.