Refine your search
Collections
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Bhatia, Madhulika
- A Proposed Stratification Approach for MRI Images
Abstract Views :213 |
PDF Views:0
Authors
Affiliations
1 Department of Computer Science and Engineering, Amity University, Noida - 201301, Uttar Pradesh, IN
2 Department of Computer Science and Engineering, Jaypee University, Noida - 201307, Uttar Pradesh, IN
3 J S Hospital, Sector 132, Noida – 201304, Uttar Pradesh, IN
1 Department of Computer Science and Engineering, Amity University, Noida - 201301, Uttar Pradesh, IN
2 Department of Computer Science and Engineering, Jaypee University, Noida - 201307, Uttar Pradesh, IN
3 J S Hospital, Sector 132, Noida – 201304, Uttar Pradesh, IN
Source
Indian Journal of Science and Technology, Vol 8, No 22 (2015), Pagination:Abstract
Background/Objectives: To classify brain MRI Images utilizing neural system. The methodology helps the specialist to robotize the examination of MRI Images and to group them into healthy and unhealthy one. Methods/Statistical Analysis: A methodology is proposed to recognize grey matter so that unhealthy MRI images can be ordered from healthy MRI Images. Classification of Brain MRI Images on the premise of Gray matter and white matter is done utilizing Neural Network pattern recognition. The novel methodology utilizes preprocessing strategies and various filters available in matlab for viable extraction and investigation of Brain MRI Images taken from BRAINIX and Neuroimaging data repository. Findings: The work has been tested on 227 variables on fifteen patients. Out of 15 samples,70% of samples are taken for Training, 15% for validation and15% for testing. Application/Improvements: This methodology is a simple alternative to be utilized as a part of doctor's facilities and medicinal places to guide doctors as well as researchers.Keywords
Image Processing, MRI Images, Neural Network, Pattern RecognitionFull Text
- An Initiative to Identify Depression using Sentiment Analysis: A Machine Learning Approach
Abstract Views :181 |
PDF Views:0
Authors
Affiliations
1 Department of IT, Amity University, Noida – 201313, Uttar Pradesh, IN
2 FET, Manav Rachna International University, Faridabad - 121004, Haryana, IN
1 Department of IT, Amity University, Noida – 201313, Uttar Pradesh, IN
2 FET, Manav Rachna International University, Faridabad - 121004, Haryana, IN
Source
Indian Journal of Science and Technology, Vol 11, No 4 (2018), Pagination:Abstract
Objective: Online social and news media has turned into an extremely mainstream for clients to impart their insights. The objective of this paper is to propose a methodology through which sentiments can be analyzed. Methods/Statistical analysis: The sentiments are helpful for the identification of the depression. In this paper we proposed an algorithm through which tweets are extracted from twitter using R studio and then their sentiments are analyzed i.e. the scores are given to each sentiment by which we identify whether the person is depressed or not. This gives imperative data to basic leadership in different spaces. Findings: Sentiment analysis over Twitter offers associations and people a quick and powerful approach to screen the general population’s sentiments towards them and their rivals. To evaluate the assumption examination over twitter we need a dataset that is been extracted from the twitter that would be publicly available for twitter sentiment analysis. We found that through twitter to extract tweets are scored based on their sentiments. The result is unique as we have proposed new algorithm through which twitter sentiments are scored. Applications: This sentiment analysis will be helpful to draw conclusion, whether the person is depressed or not. It can be helpful for prescreening test, diagnostic tool and automation monitoring system.Keywords
Depression, Sentiment Analysis, Tweets, TwitterFull Text