Aditya C R

• Doctor of Philosophy
• Professor (Associate) at Vidyavardhaka College Of Engineering

Background: Machine learning and data mining techniques have been successfully applied on MRI images for detecting Alzheimer's disease (AD). But only a few studies have explored the possibility of AD detection from non-image data. These studies have applied traditional data visualization and classification algorithms. There is a need for new sophis...

Coronary artery calcification (CAC) could assist in the discovery of new risk elements for coronary artery disorder. CAC evaluation, on the other hand, is difficult due to the wide range of CAC in the populations. As a reason, evaluating and analysing data among research have become complicated. In the Research of Inherited Risk Factors for Coronar...

Medical Resonance Imaging (MRI) is non-radioactive-based medical imaging that provides a super-resolution of tissues. However, because of its complex nature using existing Deep Learning-based noise removal (i.e., Denoising) techniques, the reconstruction quality is poor and time-consuming. An extensive study shows very limited work has been done on...

The objective of the research work is to accurately segment multiple sclerosis (MS) lesions in brain Magnetic Resonance Imaging (MRI) of varying sizes and also to classify its types. Designing effective automatic segmentation and classification tool aid the doctors in better understanding MS lesion progressions. In meeting research challenges, this...

In deep learning, it is possible that training efficiency will suffer as a result of redundant data. A lower amount of training data, on the other hand, may result in a model that is unable to capture the necessary features hidden within the dataset. In this paper, we use machine-deep-statistical model to analyse the stability of thermal storage sy...

A prevailing disease which strikes a multitude of people in the present era is Alzheimer’s Disease. Alzheimer’s Disease is a neurodegenerative disorder that causes the death of brain cells destroying memory and thinking abilities gradually. To limit the number of Alzheimer’s illness, a few frameworks have been recommended to some extent in recent t...

Parkinson's disease is a central nervous-system disorder. 90% of people with parkinson disease are reported to have speech and voice disorders. Vocal folds are normally weakened by this disorder and the patient talks improperly. Various elements of the speech patterns of healthy people and those with parkinson disease were studied for prediction of...

Individual Personality can be predicted by using Online Social Networks. The Predicted personality finds its application in various fields. This paper proposes a system to predict the personality scores of the student without having to go through any personality analysis or taking any personality test. The results obtained clearly indicate that mac...

Social media behavior of a user can be a strong indicator of one‘s personality. Personality prediction is proved to be useful in various fields such as advertisement, user interface design and recommendation systems, matrimonial and dating websites and many more. In this paper we explore various Personality Prediction Models and the effect of diffe...

Parkinson's disease is a neurodegenerative disorder that affects millions of people around the globe. Detecting Parkinson's disease at an earlier stage could help to better diagnose the disease. Machine learning provides potentially large opportunities for computer-aided identification and diagnosis that could minimize unavoidable health care error...

In this paper an exploratory data analysis model is proposed to create a suitable reference knowledge base from Alzheimer's disease dataset. The knowledge of the reference base is expressed in terms of zones with each zone carrying a weightage factor. The learnt knowledge is used to quantify the similarity of a test sample with respect to the demen...