Machine learning based data pre-processing for the purpose of medical data mining and decision support

Building an accurate and reliable model for prediction for different application domains, is one of the most significant challenges in knowledge discovery and data mining. Sometimes, improved data quality is itself the goal of the analysis, usually to improve processes in a production database and the designing of decision support. As medicine moves forward there is a need for sophisticated decision support systems that make use of data mining to support more orthodox knowledge engineering and Health Informatics practice. However, the real-life medical data rarely complies with the requirements of various data mining tools. It is often inconsistent, noisy, containing redundant attributes, in an unsuitable format, containing missing values and imbalanced with regards to the outcome class label.Many real-life data sets are incomplete, with missing values. In medical data mining the problem with missing values has become a challenging issue. In many clinical trials, the medical report pro-forma allow some attributes to be left blank, because they are inappropriate for some class of illness or the person providing the information feels that it is not appropriate to record the values for some attributes. The research reported in this thesis has explored the use of machine learning techniques as missing value imputation methods. The thesis also proposed a new way of imputing missing value by supervised learning. A classifier was used to learn the data patterns from a complete data sub-set and the model was later used to predict the missing values for the full dataset. The proposed machine learning based missing value imputation was applied on the thesis data and the results are compared with traditional Mean/Mode imputation. Experimental results show that all the machine learning methods which we explored outperformed the statistical method (Mean/Mode).The class imbalance problem has been found to hinder the performance of learning systems. In fact, most of the medical datasets are found to be highly imbalance in their class label. The solution to this problem is to reduce the gap between the minority class samples and the majority class samples. Over-sampling can be applied to increase the number of minority class sample to balance the data. The alternative to over-sampling is under-sampling where the size of majority class sample is reduced. The thesis proposed one cluster based under-sampling technique to reduce the gap between the majority and minority samples. Different under-sampling and over-sampling techniques were explored as ways to balance the data. The experimental results show that for the thesis data the new proposed modified cluster based under-sampling technique performed better than other class balancing techniques.In further research it is found that the class imbalance problem not only affects the classification performance but also has an adverse effect on feature selection. The thesis proposed a new framework for feature selection for class imbalanced datasets. The research found that, using the proposed framework the classifier needs less attributes to show high accuracy, and more attributes are needed if the data is highly imbalanced.The research described in the thesis contains the flowing four novel main contributions.a) Improved data mining methodology for mining medical datab) Machine learning based missing value imputation methodc) Cluster Based semi-supervised class balancing methodd) Feature selection framework for class imbalance datasetsThe performance analysis and comparative study show that the use of proposed method of missing value imputation, class balancing and feature selection framework can provide an effective approach to data preparation for building medical decision support

ALIGNING ASSESSMENT WITH OUTCOME BASED ASSESSMENT: AN EMPIRICAL STUDY ON UNDERGRADUATE COURSE ON FUNDAMENTALS OF STATISTICS

Since the Institution of Engineers, Bangladesh (IEB) has made Outcome Based Assessment (OBA) compulsory towards program accreditation it has been one of the vital interests of most engineering departments in Bangladesh. When considering the mapping of the Course outcome (CO) to Program Outcomes (PO) implementation of the OBA may not be an easy task. This paper reports the analysis procedure of the CO and PO achievement for an B.Sc. course on Fundamentals of Statistics, a subject, which is part of curriculum of Electrical & Electronics Engineering and Computer Science and Engineering at Eastern University, Bangladesh. As a sum, this paper contributes complete process and an example investigation for Outcome Based Valuation starting from course curriculum progress to its CO-PO achievement based on definite criteria.  Article visualizations

STUDY OF HOMOGENEITY, POROSITY AND INTERNAL DEFECTS IN AERATED AND EPS AGGREGATE POLY BRICKS USING NEUTRON RADIOGRAPHY TECHNIQUE

A powerful non-destructive testing (NDT) technique is adopted to study the internal defects and elemental distribution/homogeneity and porosity of aerated brick and EPS aggregate poly brick samples. In the present study the internal defects like homogeneity, porosity, elemental distribution, EPS aggregate and aerator distributor in the test samples have been observed by the measurement of gray value/optical density of the neutron radiographic images of these samples. From this measurement it is found that the neutron intensity/optical density variation with the pixel distance of the AOI of the NR images in both expanded polystyrene (EPS) aggregate poly brick and aerated brick samples comply almost same in nature with respect to the whole AOI but individually each AOI shows different nature from one AOI to another and it confirms that the elemental distribution within a AOI is almost homogeneous. Finally it was concluded that homogeneity, elemental distribution in the EPS aggregate poly brick sample is better than that of the aerated brick sample

Digital Resources Management in Libraries: Step towards digital Bangladesh

The purpose of this paper is to investigate the existing digital resource management systems and practices in Bangladeshi libraries. This paper followed a mixed research approach and collected primary data by questionnaire method. It explored the library professionals' conception about digital library and institutional repository that best fit in Bangladesh context and their practices. The findings indicate that there is an enormous development in library digitization initiatives in the last decade. The libraries are facing challenges like capacity building, declining budgets, insufficient facilities, and traditional functions knocked by modern technologies. Despite many obstacles, the library professionals are leading from the front in digitization projects and implementing digital resource management systems. This paper also discusses some issues, for instance, digital library, institutional repository, open source software, metadata, vocabulary, open access vs close access, copyright issues, user’s needs, user interface, virtual reference, organizational policy, barriers, etc., and suggested a set of practical guidelines and proposed collaborative digitization initiatives

Biological and quantitative-SAR evaluations, and docking studies of (E)-N'-benzylidenebenzohydrazide analogues as potential antibacterial agents

A series of 15 (E)-N'-benzylidenebenzohydrazide analogues were evaluated for their antimicrobial activities against eleven pathogenic and food-borne microbes, namely, S. aureus (G+), L. monocytogenes (G+), B. subtilis (G+), K. pneumonia (G-), C. sakazakii (G-), C. freundii (G-), S. enterica (G-), S. enteritidis (G-), E. coli (G-), Y. pestis (G-), and P. aeruginosa (G-). Most of the compounds exhibited selective activity against some Gram-negative bacterial strains. Of the compounds tested (3a-o), 3b and 3g were most active against C. freundii (MIC = ~19 µg mL-1). Whereas, compounds 3d, 3i, 3k and 3n exhibited MIC values ranging from 37.5 to 75 µg mL-1 against C. freundii, and compounds 3e, 3l and 3n had MIC values of ~75 µg mL-1 against K. pneumonia. Quantitative structure-antibacterial activity relationships were studied using physicochemical parameters and a good correlation was found between calculated octanol-water partition coefficients (clogP; a lipophilic parameter) and antibacterial activities. In silico screening was also performed by docking high (3b and 3g) and low (3n) activity compounds on the active site of E. coli FabH receptor, which is an important therapeutic target. The findings of these in silico screening studies provide a theoretical basis for the design and synthesis of novel benzylidenebenzohydrazide analogues that inhibit bacterial FabH

Cross linked Core-shell Silica Nanoparticles Mechanical, Structural & Viscoelastic Behavior

Shell cross-linked core-shell nanoparticles (SCCSNs) were prepared via miniemulsion polymerization of styrene in the presence of silane modified inorganic silica. The polystyrene (PS) shell of 69.8% in weight fraction was cross-linked using divinylbenzene. SCCSNs were spherical with a diameter distribution from 37 to 96 nm determined by dynamic light scattering. Dynamic rheology of SCCSNs suspended in PS/toluene solution was compared with that of suspensions of naked silica. The critical strain for onset of rheological nonlinearity was independent of SCCSN concentration above a concentration threshold, which differs from the silica suspensions. Linear dynamic rheological investigation revealed that SCCSN suspensions with a PS volume fraction of 25% were fluid-like at low particle concentrations while suspensions containing 4.5 vol% SCCSNs formed a gel-like structure. On the contrary, the silica suspensions with 20.0 vol% PS underwent a fluid-to-solid-like transition with increasing silica concentration. Reasons for the different rheological behaviors of the naked silica and SCCSN suspensions are discussed

A review on Antibacterial Coloration Agent’s Activity, Implementation & Efficiency to Ensure the Ecofriendly & Green Textiles

Recently antibacterial colorants are most important research topic to the researchers. With high biodegradability, low toxicity, green chemistry and having potential application they exhibit a great impact on the textile dyeing and finishing industry. Natural colorants from plant sources either extraction or synthesis have been recently revealed as novel agents in imparting multifunctional properties to textiles such as antimicrobial, insect repellent, deodorizing, even UV protection. Many colorants, whether natural or synthetic, possess some inherent functions in addition to their coloring attribution. These properties can be utilized in textile dyeing processes to bring the particular functions to textiles in various textile industries. In other words, dyeing textiles with these colorants can combine dyeing with having a functionality finishes, a greener process than current separated wet treatments in terms of reduced generation of waste water and consumption of energy. Recently there has been a revival of interest in the use of natural dyes in textile coloration. This is a result of the stringent environmental standards imposed by many countries in response to the toxic and allergic reactions associated with the use of synthetic dyes. The aim of this review compilation is to give an overview on the main compounds used today for coloration of textile materials seeking for as antibacterial functionalization based on an evaluation of scientific publications, potential perspective of microbes on the environment and human health were considered

Cluster of Nipah Virus Infection, Kushtia District, Bangladesh, 2007

OBJECTIVE: In March 2007, we investigated a cluster of Nipah encephalitis to identify risk factors for Nipah infection in Bangladesh. METHODS: We defined confirmed Nipah cases by the presence of IgM and IgG antibodies against Nipah virus in serum. Case-patients, who resided in the same village during the outbreak period but died before serum could be collected, were classified as probable cases. RESULTS: We identified three confirmed and five probable Nipah cases. There was a single index case. Five of the secondary cases came in close physical contact to the index case when she was ill. Case-patients were more likely to have physical contact with the index case (71% cases versus 0% controls, p = <0.001). The index case, on her third day of illness, and all the subsequent cases attended the same religious gathering. For three probable cases including the index case, we could not identify any known risk factors for Nipah infection such as physical contact with Nipah case-patients, consumption of raw date palm juice, or contact with sick animals or fruit bats. CONCLUSION: Though person-to-person transmission remains an important mode of transmission for Nipah infection, we could not confirm the source of infection for three of the probable Nipah case-patients. Continued surveillance and outbreak investigations will help better understand the transmission of Nipah virus and develop preventive strategies

Investigation of heavy metal contents in Cow milk samples from area of Dhaka, Bangladesh

Background: Cow milk is considered as one of the responsible food sources contaminated with heavy metals. The objectives of the study were to assess the content of selected metals in cow milk and its associated human health risks in the food chain of Bangladesh. A total of 90 cow milk samples of Branded, Dairy and Domestically produced milk were collected randomly from different sources of Savar Upazila in Dhaka area. Cadmium (Cd), chromium (Cr), lead (Pb), manganese (Mn), copper (Cu) and iron (Fe) contents in collected milk samples were determined using Flame Atomic Absorption Spectrometry (FAAS). To ensure quality control, one of the best quality control parameters i.e. recovery test; from eight various sample digestion methods were used. The Hazard Quotient (HQ) and Carcinogenic Risk (CR) values were also calculated. Results: From the results, it was found that, the orders of heavy metal content in brand, dairy and domestic cow milk were Cr > Fe > Cu>Mn > Cd > Pb, Cr > Fe > Mn > Cu > Cd > Pb and Fe > Cr > Mn > Cu > Cd > Pb, respectively. Among the six metals, only Cr showed to exceed the highest Estimated Daily Intake (EDI) rate (for brand cow milk: 0.413 mg/day, dairy farm cow milk: 0.243 mg/day, domestic cow milk: 0. 352 mg/day),and the comparison percentages of calculated values per permeable values were as follows; 206.5 % for brand cow milk,121.5 % for dairy farm cow milk and 176.0 % for domestic cow milk. Hazard Quotients (HQ) values and Carcinogenic Risk (CR) values were found within the acceptable level. Conclusion: Although, the metal content in sampled cow milks were within the safe limit, the potential human health risks cannot be neglected for the regular/long time consumption of heavy metal contained cow milk