An under-Sampled Approach for Handling Skewed Data Distribution using Cluster Disjuncts

In Data mining and Knowledge Discovery hidden and valuable knowledge from the data sources is discovered. The traditional algorithms used for knowledge discovery are bottle necked due to wide range of data sources availability. Class imbalance is a one of the problem arises due to data source which provide unequal class i.e. examples of one class in a training data set vastly outnumber examples of the other class(es). Researchers have rigorously studied several techniques to alleviate the problem of class imbalance, including resampling algorithms, and feature selection approaches to this problem. In this paper, we present a new hybrid frame work dubbed as Majority Under-sampling based on Cluster Disjunct (MAJOR_CD) for learning from skewed training data. This algorithm provides a simpler and faster alternative by using cluster disjunct concept. We conduct experiments using twelve UCI data sets from various application domains using five algorithms for comparison on six evaluation metrics. The empirical study suggests that MAJOR_CD have been believed to be effective in addressing the class imbalance problem

Pharmacoenvironmentology – a component of pharmacovigilance

According to WHO, Pharmacovigilance activities are done to monitor detection, assessment, understanding and prevention of any obnoxious adverse reactions to drugs at therapeutic concentration on animal and human beings. However, there is also a growing focus among scientists and environmentalists about the impact of drugs on environment and surroundings. The existing term 'Ecopharmacology' is too broad and not even defined in a clear manner. The term 'Pharmacoenvironmentology' seeks to deal with the environmental impact of drugs given to humans and animals at therapeutic doses

Evaluation of dose dependent analgesic response by extracts of Myristica fragrans on albino wistar rats: an experimental study

Background: The objective of the study was to evaluate analgesic activity of ethanolic extract, methanol and benzene fraction of Myristica fragrans on wistar albino rats.Methods: The present study was carried out in the department of pharmacology JNMC AMU and F.H. Medical College, Agra. The analgesic activity was evaluated by employing the Eddy’s hot plate method and tail flick response method. In both the tests, Rats of either sex weighing 150-200 g were used. The total number of animals n=36 were allocated to six groups. Each group consist of six animals each. The response noted in animals that were tested by hot plate method was reaction time for licking/biting of both the paws before and after administration of control & test drugs. However in Tail flick test, the pain threshold response was recorded before and after administration of control & test drugs. The statistical analysis was done by using one-way ANOVA. The data is expressed as Mean±SEM. P<0.05 was considered to be statistically significant.Results: Ethanolic extracts and methanol fraction of M. fragrans showed statistically significant (p<0.001) increase in reaction time for licking/biting in hot plate method. On the contrary a significant increase in pain threshold was also recorded in tail flick response test. It is interesting to note that no significant degree of analgesia related to any dose of benzene fraction was observed.Conclusions: The present study reveals the dose dependent significant analgesic activity of the extracts of M. fragrans i.e. ethanolic extracts and methanol fraction in both the test. However, the degree of analgesia was recorded significantly higher in groups received higher doses of extracts of M. fragrans

Applications of Machine Learning for Fake News Detection in Social Networks

The value of online media for getting news is questionable. People seek out and devour news from online media because it is convenient, inexpensive, and widely disseminated. In contrast, it facilitates the widespread distribution of "counterfeit news," or news of lower quality that includes fabricated data. Many people and institutions are negatively impacted by the widespread circulation of false information. As a result, detecting fake news via social media has emerged as a topic of interest for academics. Searching for and reading the news is becoming increasingly convenient as a result of the widespread availability, quick expansion, and widespread dissemination of traditional news outlets and social media. Nowadays, there is a plethora of information that can be found on social media, and it can be difficult to tell what is real and what is not. The distribution costs of releasing news via social media are inexpensive, and anyone can do it. The widespread circulation of false information could have devastating effects on both individuals and communities. Developing a reliable machine learning method for spotting fake news is the focus of this work

Association of C-reactive protein with bacterial and respiratory syncytial virus-associated pneumonia among children aged <5 years in the PERCH study

Background. Lack of a gold standard for identifying bacterial and viral etiologies of pneumonia has limited evaluation of C-reactive protein (CRP) for identifying bacterial pneumonia. We evaluated the sensitivity and specificity of CRP for identifying bacterial vs respiratory syncytial virus (RSV) pneumonia in the Pneumonia Etiology Research for Child Health (PERCH) multicenter case-control study. Methods. We measured serum CRP levels in cases with World Health Organization-defined severe or very severe pneumonia and a subset of community controls. We evaluated the sensitivity and specificity of elevated CRP for "confirmed" bacterial pneumonia (positive blood culture or positive lung aspirate or pleural fluid culture or polymerase chain reaction [PCR]) compared to "RSV pneumonia" (nasopharyngeal/oropharyngeal or induced sputum PCR-positive without confirmed/suspected bacterial pneumonia). Receiver operating characteristic (ROC) curves were constructed to assess the performance of elevated CRP in distinguishing these cases. Results. Among 601 human immunodeficiency virus (HIV)-negative tested controls, 3% had CRP ≥40 mg/L. Among 119 HIVnegative cases with confirmed bacterial pneumonia, 77% had CRP ≥40 mg/L compared with 17% of 556 RSV pneumonia cases. The ROC analysis produced an area under the curve of 0.87, indicating very good discrimination; a cut-point of 37.1 mg/L best discriminated confirmed bacterial pneumonia (sensitivity 77%) from RSV pneumonia (specificity 82%). CRP ≥100 mg/L substantially improved specificity over CRP ≥40 mg/L, though at a loss to sensitivity. Conclusions. Elevated CRP was positively associated with confirmed bacterial pneumonia and negatively associated with RSV pneumonia in PERCH. CRP may be useful for distinguishing bacterial from RSV-associated pneumonia, although its role in discriminating against other respiratory viral-associated pneumonia needs further study