Abraham Varghese

• Msc (Mathematics), BED, M Tech, PhD
• Senior Lecturer at University of Technology and Applied Sciences Muscat

Background This study explores Alzheimer’s prediction through brain MRI images, utilizing Convolutional Neural Networks (CNNs) and Lime interpretability. Based on an extensive ADNI MRI dataset, we demonstrate promising results in predicting Alzheimer’s disease. Local Interpretable Model Agnostic Explanations (LIME) shed light on decision‐making pro...

Background Recent breakthroughs in Quantum Calculus (QC) have given new opportunities for texture analysis. Motivated by QC, QELBP examines subtle variations in grayscale within MRI, which may provide early signs of textural changes associated with AD. Method 13500 images were extracted from 150 images (90 slices/patient). Texture descriptors LBP...

Background Early detection and personalized care for Alzheimer’s Disease (AD) mitigate the devastating consequences for millions of people around the globe. In the current scenario, there is a lack of user‐friendly AI applications for predicting and understanding the progression of AD. The application should address the critical need for a predicti...

Alzheimer’s disease, acknowledged for its intricate and degenerative characteristics, presents considerable challenges, particularly among the elderly population. The relentless nature of Alzheimer’s, marked by the gradual deterioration of cognitive function, underscores the urgency to develop effective strategies for early diagnosis and interventi...

Background Alzheimer’s disease (AD) results in cognitive dysfunction among older people, making their lives nearly impossible. Early intervention is likely to be the most effective way to slow its progression. Machine learning models are critical to determine whether a patient is demented or not at an early stage. But the most highly accurate model...

The present novel coronavirus (COVID-19) infection has engendered a worldwide crisis on an enormous scale within a very short period. The effective solution for this pandemic is to recognize the nature and spread of the disease so that appropriate policies can be framed. Mathematical modelling is always at the forefront to understand and provide an...

Objective: To develop and validate a clinical score that will identify potential admittance in an intensive care unit (ICU) for a coronavirus disease 2019 (COVID-19) case. Materials and methods: The clinical scoring is built using Least Absolute Shrinkages and Selection Operator logistic regression. The prediction algorithm was constructed and c...

The present novel corona virus (COVID-19) infection has engendered a worldwide crisis across the world in an enormous scale within a very short period. The effective solution for this pandemic is to recognize the nature and spread of the disease so that appropriate policies can be framed. Mathematical modelling is always at the forefront to underst...

This study is conducted to investigate experts’ views to determine the Omani higher education institutions readiness and deployment of IPv6. In particular, the study aims to assess the institutional awareness, current environment, policy, planning, and resources. Descriptive method was followed and two study instruments were designed and implemente...

This study is conducted to investigate experts' views to determine the Omani higher education institutions readiness and deployment of IPv6. In particular, the study aims to assess the institutional awareness, current environment, policy, planning, and resources. Descriptive method was followed and two study instruments were designed and implemente...

During the learning process, whether students remain attentive throughout the session influences their learning capability. If teachers can identify whether students are attentive they can be notified to remain focused, thus resulting in improving their learning capability. Traditional methods require, teachers observe students’ facial expressions...

Concentration level monitoring in education and healthcare Abraham Varghese 1; Ali Al Musawi 2; Sunil Jacob 3; Jibin Lukose 3 1Information Technology Department, Higher college of Technology, Muscat, Sultanate of Oman; 2Department of Instructional and Learning Technologies (ILT), Sultan Qaboos University, Muscat, Oman; 3 SCMS Centre for Robotic...

This paper describes the first stage of an internal grant provided by the Sultan Qaboos University to conduct a research project exploring the actual readiness of Higher Education Institutions (HEIs) to adopt a national migration plan to IPv6. Document analysis was used to derive necessary data on steps taken by the Omani concerned authorities to p...

In this era of information technology, email applications are the foremost and extensively used electronic communication technology. Emails are profusely used to exchange data and information using several frontend applications from various service providers by its users. Currently most of the email clients and service providers now moved to secure...

Outcome Based Education (OBE) or student centered learning is one of the key component in quality assurance and enhancement in the higher education. The OBE approach encourages students to become active learner rather than being passive as in the traditional teacher-centered learning approach. In OBE, teacher is a facilitator of the teaching learni...

Image hashing technique constructs a short sequence from the image to represent its contents. This method proposes an image hash which is generated from Haralick and MOD-LBP features along with luminance and chrominance, which are computed from Zernike moments. Sender generates the hash from image features and attaches it with the image to be sent....

Noise in an image is variation of information from the actual data. If there is any noise in the medical image then consequence will be huge. Physician won't be able to do proper diagnose of the disease and can also affects the quality of post processing techniques like registration and segmentation. Modern techniques use multiple coil MRI(Magnetic...

Modern digital world produces massive amount of data generally refereed as Big Data, which play important roles in dictating the quality of our lives. Relationships among such data have high value, but extremely complex task to establish. Medical Field is one of the major big data sources which produces big volume of data. Modern surgical tools hav...

The medical imaging technology plays a crucial role in visualization and analysis of the human body with unprecedented accuracy and resolution. Analyzing the multimodal for disease-specific information across patients can reveal important similarities between patients, hence their underlying diseases and potential treatments. Classification of MR b...

Alzheimer's disease (AD) is a Dementia among older people which causes neurological degradation. Mild Cognitive Impairment [1] (MCI) is a condition which could progress and then become AD but is not explicitly visible in one's behavior. This paper presents a strategic approach for recognizing MCI at early stage using Magnetic Resonance Imaging (MRI...

Retrieval of similar anatomical structures of brain MR images across patients would help the expert in diagnosis of diseases. In this paper, modified local binary pattern with ternary encoding called modified local ternary pattern (MOD-LTP) is introduced, which is more discriminant and less sensitive to noise in near-uniform regions, to locate slic...

Magnetic Resonance images play a crucial role in the diagnosis and management of the diseases of the brain. The MRI can acquire cross sectional images of our body, based on T1 and T2 relaxation of the tissues. As the information presented in these two images is often complimentary, both these images need to be compared for accurate clinical diagnos...

An intelligent classification technique for MR brain images are extremely important for medical analysis and treatment selection. Manual interpretation of these images by physicians may lead to wrong diagnosis when a large number of MRIs are analyzed. In this paper an automated decision support system for classification is proposed. It consists of...

decision-diagnosis process of brain MR images. For an accurate diagnosis of brain related problems, the experts mostly compares both T1 and T2 weighted images as the information presented in these two images are complementary. In this paper, rotational and translational invariant form of Local binary Pattern (LBP) with additional gray scale informa...

Magnetic resonance images play a vital role in identifying various brain related problems. Some of the diseases of the brain show abnormalities predominately at a particular anatomical location which on MR appears at a slice at defined level. This paper proposes a novel technique to locate desired slice using Rotational, Scaling and Translational (...

Axial brain slices containing similar anatomical structures are retrieved using features derived from the histogram of Local binary pattern (LBP). A rotation invariant description of texture in terms of texture patterns and their strength is obtained with the incorporation of local variance to the LBP, called Modified LBP (MOD-LBP). In this paper,...

Some common fixed point theorems for non-self hybrid mappings have been proved by altering the distance between the points. Our results extends and generalizes many well known results.