Novel Method Of Disease Prediction Using Machine Learning And Hand Gesture.
Authors: C. Krithika, Pradeep
Abstract
Analysis of various symptoms and finally diagnosing the possible disease is an important issue nowadays. This
paper focuses on the application and development of input based assistants to solve the problems of
physically challenged persons by accepting gestures which could be used for feature detection , extraction and
finally matching with the clusters made. The image classification is supposed to be done using convolution neural
networks. And the diseases prediction process is based on the well known machine learning algorithm such as
DecisionTree . Naive Bayes and Random Forest and by using these algorithm diseases can be used to predict
more accurately.
Keywords: Gesture recognition,Image Processing, Naive Bayes technique
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Pages: 01-05
2nd Article
Methods For The Detection Of Parkinson’s Disease – A Review
Authors: Ashok, Balaji
AbstractParkinson's disease (PD) is a neurodegenerative disorder which often affects patients' movements. Some
of the most common symptoms of Parkinson’s disease are tremors, rigidity, akinesia, walking
disability, and postural instability. The primary motor symptoms are collectively called
“parkinsonism”. This review aims to evaluate the various techniques used in detecting Parkinson’s
Disease with the aid of data mining algorithms such as Multiple Instance Learning (MIL), K-means
clustering, Decision Tree Classification, Moving Average Algorithm . The accuracies and
drawbacks of these techniques also gives an outline of the proposed system. Since all of the existing
models consider a single symptom for detecting Parkinson’s, the proposed approach aims at building an
analytical model with two different symptoms i.e. speech and finger tapping keystroke, so as to increase
the accuracy and find the co-relation between these symptoms.
Keywords. Parkinson’s disease, data mining, SVM, Logistic regression, keystroke.
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Pages: 06 - 12
3rd Article
The Key To Universal Health Coverage – An Overview
Authors: kaviya, Meenatchi
AbstractThe first time World Health Organization pinned Universal Health Coverage (UHC) as a focal point was
in the year 2010 in their World Health Report. Since then UHC has been a heated topic of discussion
among researchers, academicians, industry experts and the governments across the globe including India
(Greer & Mendez, 2015). The aim of the present study is to implement levels of key recommendations
proposed by the High Level Expert Group (HLEG) for UHC in India and to recommend suggestions for
achieving maximum UHC in India. According to the World Health Statistics of 2017, there are seven
factors that have been taken into account in order to monitor health for Sustainable Development Goals
(SDGs). One of these seven factors is Universal Health Coverage (World Health Statistics, 2017)
Keywords: Universal Health Coverage, Health Insurance, HLEG, Health Insurance Schemes.
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Pages:13-22
4th Article
Role Of Digitalization In Spreading Awareness On Corona Virus
Authors: Manojkumar, Ramya
AbstractToday the social media is the part of everyone in the world. Most of the smartphone users are having at
least one social media account to post their feelings and emotions. These emotions will bring the
sentiments of various peoples living from different parts of the world. The sentiments are vary depending
on the living condition and traditional culture. Also the sentiment can give a global knowledge to the
society to understand the current situations and reactions given on the social media. The present study
focusses on the role of digital world in creating awareness to the society on corona virus. In large
number of social media the Twitter is one among the most popular tool used by most of the users in the
society. The current world trending news is all about the Covid-19, hence the messages given on the
twitter are analyzed for predicting the number of peoples affected on this corona virus. The Covid-19
can be categorized in different stages by healthcare experts as early stage, middle and severe stages. The
text on Twitter can be analyzed and predicted the number of peoples affected on this disease. The results
of the study are very useful to the government and social service organizations to attack the problems and
bring the notice to the public to keep distance from the affected peoples and taking precautions for good
health. This paper will discuss about the Twitter data analysis on Corona virus using python packages
such as NLTK, Scikit-learn, etc.
Keywords: Social media, Twitter, Covid-19, Corona virus, NLTK.
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Pages:23-27
5th Article
Tools For The Prediction Of Coronary Heart Disease - A Survey
Authors: Pradheep,
Rajesh
Abstract
It is important to save lives by detecting the heart disease earlier.Machine Learning then Data Mining is
used as a aid contraptions by using providing the essential data and classification in accordance with
diagnose a heart disease, primarily based on concerning the given input data. The present study analyses a
systematic literature review based on journal articles published since 2012. The current study aims to
estimate and analyse the use of specific machine learning and mining techniques for the prediction of
coronary heart disease. This study significantly analyses the chosen papers and finds gaps between the
current literature yet is helpful because researchers anybody want in accordance with apply machine
learning algorithms among clinical domains, especially concerning heart disease datasets. This survey
finds oversee that prediction exactness beyond most popular machine learning algorithms permanency
like Random Forest, Decision Trees, and K-Nearest Neighbours.