21 research outputs found

    A Robust Cardiovascular Disease Predictor Based on Genetic Feature Selection and Ensemble Learning Classification

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    Timely detection of heart diseases is crucial for treating cardiac patients prior to the occurrence of any fatality. Automated early detection of these diseases is a necessity in areas where specialized doctors are limited. Deep learning methods provided with a decent set of heart disease data can be used to achieve this. This article proposes a robust heart disease prediction strategy using genetic algorithms and ensemble deep learning techniques. The efficiency of genetic algorithms is utilized to select more significant features from a high-dimensional dataset, combined with deep learning techniques such as Adaptive Neuro-Fuzzy Inference System (ANFIS), Multi-Layer Perceptron (MLP), and Radial Basis Function (RBF), to achieve the goal. The boosting algorithm, Logit Boost, is made use of as a meta-learning classifier for predicting heart disease. The Cleveland heart disease dataset found in the UCI repository yields an overall accuracy of 99.66%, which is higher than many of the most efficient approaches now in existence

    Behavioural Pattern of School Students towards E-learning Platform during Covid-19 period with special reference to Coimbatore city

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    E-learning has taken it full fudged emergence with regards to Covid Scenario. Also, the lockdown of schools and playgrounds, the restriction of outdoor activities, physical and social isolation leads to the behavioural change among school children. Students are more attached to their schools, teachers and friends. But Covid 19 has changed the entire situation changed and they were held in their home itself. Students were not able to meet their friends and teachers, they especially miss their school and class environment. It is to be noted that maintaining social isolation and following “Stay at Home” plays a very high impact among school students. Also, the lockdown created for families and children sit inside their homes. Which ,We cannot leave children’s education as it is. In order to continue their education, Indian Government has taken many efforts .Even schools are doing their best to bridge the gap between teachers and students by providing online education because of the absence of regular classroom education. Because of the introduction of online class by schools, on the one side students are not missing the education, on the other side students and parents faces a lot of problems (Physical and mental. It also puts them at the risk of unsupervised access to websites and other unwanted sites in internet

    Comparision of Different Classifiers for Prediction of Breast Cancer

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    The cell formed in the  breast are known as breast cancer. It occurs mainly in women and it may occur rarely in men also. It is considered as the most common ailment that can lead to large number of death in females every year. In spite of the factuality that cancer is treatable and can be relieve if treated at its early stages; many patients are screened for cancer only at a very late stage. Data mining technique such as classifications provides an efficient technique to classify data, where these methods are commonly used for diagnostic decision making. The Machine learning techniques propound various methods such as statistical and probabilistic methods which allow system to learn from past experiences to distinguish and identify patterns from a standard dataset. The research work presents a review of machine learning techniques which can be used in breast cancer disease detection by applying algorithms on breast cancer Wisconsin data set.  Algorithms such as Navies Bayes, Random Forest, Support Vector Machine, Adaboost and Decision Trees were used. The result outcome shows that Random Forest performs better than other techniques

    Recent Advanced Computing Methods Employed in Web Service Automation - A Survey

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    Web Service Automation gains momentum for the past two decades. So, various computational algorithms have been developed on different aspects of web service categorization and resource allocation. Research activities are more on comparing the algorithms over time and space complexity. Web designers and service providers make their contribution to enrich the IT products in this area. In this paper, a detail study is attempted on the above aspects of web service Automation. We open an area of web technology for implementation of newer algorithms. Keywords - Web Service Allocation, Zero Knowledge Authentication, Logic Programming, Service Computing, Distributed Algorithms, Cloud computing

    Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

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    Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

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