All Outputs (37)

Early dementia detection with speech analysis and machine learning techniques (2024)
Journal Article
Jahan, Z., Khan, S. B., & Saraee, M. (in press). Early dementia detection with speech analysis and machine learning techniques. #Journal not on list, 5(1), 65. https://doi.org/10.1007/s43621-024-00217-2

This in-depth study journey explores the context of natural language processing and text analysis in dementia detection, revealing their importance in a variety of fields. Beginning with an examination of the widespread and influence of text data. Th... Read More about Early dementia detection with speech analysis and machine learning techniques.

User-centric secured smart virtual assistants framework for disables (2024)
Journal Article
Alfayez, F., & Khan, S. B. (in press). User-centric secured smart virtual assistants framework for disables. Alexandria engineering journal : AEJ, 95, 59-71. https://doi.org/10.1016/j.aej.2024.03.033

Research on intelligent secured virtual assistant (ISVA) systems for disabled people is essential in order to meet the special requirements and overcome the difficulties they confront. The delicate nature of user interactions makes... Read More about User-centric secured smart virtual assistants framework for disables.

A New Approach for Speech Emotion Recognition using Single Layered Convolutional Neural Network (2024)
Journal Article
Vinoth Kumar, V., Palaiahnakote, S., Khan, S. B., & Almusharraf, A. (in press). A New Approach for Speech Emotion Recognition using Single Layered Convolutional Neural Network. Malaysian journal of computer science,

Creating a computational device to identify human emotions via voice analysis represents a notable achievement in the sector of human-computer interaction, especially within the healthcare domain. We propose a new lightweight model for addressing cha... Read More about A New Approach for Speech Emotion Recognition using Single Layered Convolutional Neural Network.

Advances in real time smart monitoring of environmental parameters using IoT and sensors (2024)
Journal Article
Narayana, T. L., Venkatesh, C., Kiran, A., J, C. B., Kumar, A., Khan, S. B., …Quasim, M. T. (in press). Advances in real time smart monitoring of environmental parameters using IoT and sensors. Heliyon, 10(7), e28195. https://doi.org/10.1016/j.heliyon.2024.e28195

People who work in dangerous environments include farmers, sailors, travelers, and mining workers. Due to the fact that they must evaluate the changes taking place in their immediate surroundings, they must gather information and da... Read More about Advances in real time smart monitoring of environmental parameters using IoT and sensors.

Hybrid optimization algorithm for enhanced performance and security of counter-flow shell and tube heat exchangers (2024)
Journal Article
Kiran, A., Nagaraju, C., Babu, J. C., Venkatesh, B., Kumar, A., Khan, S. B., …Basheer, S. (in press). Hybrid optimization algorithm for enhanced performance and security of counter-flow shell and tube heat exchangers. PloS one, 19(3), e0298731. https://doi.org/10.1371/journal.pone.0298731

A shell and tube heat exchanger (STHE) for heat recovery applications was studied to discover the intricacies of its optimization. To optimize performance, a hybrid optimization methodology was developed by combining the Neural Fitting Tool (NFTool),... Read More about Hybrid optimization algorithm for enhanced performance and security of counter-flow shell and tube heat exchangers.

An Adaptive Xception Model for Classification of Brain Tumors (2024)
Journal Article
Thakur, A., Bhatia Khan, S., Palaiahnakote, S., Kumar V, V., Almusharraf, A., & Mashat, A. (in press). An Adaptive Xception Model for Classification of Brain Tumors. International Journal of Pattern Recognition and Artificial Intelligence,

Classification of different brain tumors is challenging due to unpredictable variations in intra-inter-classes. Unlike existing methods which are not effective for images of complex backgrounds, the proposed work aims at accurate classification of di... Read More about An Adaptive Xception Model for Classification of Brain Tumors.

Enhancing accessibility for improved diagnosis with modified EfficientNetV2-S and cyclic learning rate strategy in women with disabilities and breast cancer (2024)
Journal Article
Al Moteri, M., Mahesh, T. R., Thakur, A., Vinoth Kumar, V., Khan, S. B., & Alojail, M. (in press). Enhancing accessibility for improved diagnosis with modified EfficientNetV2-S and cyclic learning rate strategy in women with disabilities and breast cancer. Frontiers in Medicine, 11, 1373244. https://doi.org/10.3389/fmed.2024.1373244

Breast cancer, a prevalent cancer among women worldwide, necessitates precise and prompt detection for successful treatment. While conventional histopathological examination is the benchmark, it is a lengthy process and prone to variations among diff... Read More about Enhancing accessibility for improved diagnosis with modified EfficientNetV2-S and cyclic learning rate strategy in women with disabilities and breast cancer.

Oral squamous cell carcinoma detection using EfficientNet on histopathological images (2024)
Journal Article
Albalawi, E., Thakur, A., Ramakrishna, M. T., Bhatia Khan, S., SankaraNarayanan, S., Almarri, B., & Hadi, T. H. (in press). Oral squamous cell carcinoma detection using EfficientNet on histopathological images. Frontiers in Medicine, 10, 1349336. https://doi.org/10.3389/fmed.2023.1349336

Introduction: Oral Squamous Cell Carcinoma (OSCC) poses a significant challenge in oncology due to the absence of precise diagnostic tools, leading to delays in identifying the condition. Current diagnostic methods for OSCC have limitations in accura... Read More about Oral squamous cell carcinoma detection using EfficientNet on histopathological images.

An artificial intelligence-based decision support system for early and accurate diagnosis of Parkinson’s Disease (2024)
Journal Article
T.R., M., V., V. K., Bhardwaj, R., Khan, S. B., Alkhaldi, N., Victor, N., & Verma, A. (2024). An artificial intelligence-based decision support system for early and accurate diagnosis of Parkinson’s Disease. #Journal not on list, 10, 100381. https://doi.org/10.1016/j.dajour.2023.100381

People with Parkinson’s Disease (PD) might struggle with sadness, restlessness, or difficulty speaking, chewing, or swallowing. A diagnosis can be challenging because there is no specific PD test. It is diagnosed by doctors using a... Read More about An artificial intelligence-based decision support system for early and accurate diagnosis of Parkinson’s Disease.

Advancing Disability Management in Information Systems: A Novel Approach through Bidirectional Federated Learning-Based Gradient Optimization (2023)
Journal Article
Khan, S. B., Alojail, M., & Al Moteri, M. (in press). Advancing Disability Management in Information Systems: A Novel Approach through Bidirectional Federated Learning-Based Gradient Optimization. Mathematics, 12(1), 119. https://doi.org/10.3390/math12010119

Disability management in information systems refers to the process of ensuring that digital technologies and applications are designed to be accessible and usable by individuals with disabilities. Traditional methods face several challenges such as p... Read More about Advancing Disability Management in Information Systems: A Novel Approach through Bidirectional Federated Learning-Based Gradient Optimization.

Early Detection of Lung Nodules Using a Revolutionized Deep Learning Model (2023)
Journal Article
Srivastava, D., Srivastava, S. K., Khan, S. B., Singh, H. R., Maakar, S. K., Agarwal, A. K., …Albalawi, E. (in press). Early Detection of Lung Nodules Using a Revolutionized Deep Learning Model. Diagnostics, 13(22), 3485. https://doi.org/10.3390/diagnostics13223485

According to the WHO (World Health Organization), lung cancer is the leading cause of cancer deaths globally. In the future, more than 2.2 million people will be diagnosed with lung cancer worldwide, making up 11.4% of every primary cause of cancer.... Read More about Early Detection of Lung Nodules Using a Revolutionized Deep Learning Model.

Preservation of Sensitive Data Using Multi-Level Blockchain-based Secured Framework for Edge Network Devices (2023)
Journal Article
Awasthi, C., Mishra, P. K., Pal, P. K., Khan, S. B., Agarwal, A. K., Gadekallu, T. R., & Malibari, A. A. (2023). Preservation of Sensitive Data Using Multi-Level Blockchain-based Secured Framework for Edge Network Devices. Journal of Grid Computing, 21(4), 69. https://doi.org/10.1007/s10723-023-09699-2

The proliferation of IoT devices has influenced end users in several aspects. Yottabytes (YB) of information are being produced in the IoT environs because of the ever-increasing utilization capacity of the Internet. Since sensitive information, as w... Read More about Preservation of Sensitive Data Using Multi-Level Blockchain-based Secured Framework for Edge Network Devices.

A Deep Learning Framework with an Intermediate Layer Using the Swarm Intelligence Optimizer for Diagnosing Oral Squamous Cell Carcinoma (2023)
Journal Article
Nagarajan, B., Chakravarthy, S., Venkatesan, V. K., Ramakrishna, M. T., Khan, S. B., Basheer, S., & Albalawi, E. (in press). A Deep Learning Framework with an Intermediate Layer Using the Swarm Intelligence Optimizer for Diagnosing Oral Squamous Cell Carcinoma. Diagnostics, 13(22), 3461. https://doi.org/10.3390/diagnostics13223461

One of the most prevalent cancers is oral squamous cell carcinoma, and preventing mortality from this disease primarily depends on early detection. Clinicians will greatly benefit from automated diagnostic techniques that analyze a patient’s histopat... Read More about A Deep Learning Framework with an Intermediate Layer Using the Swarm Intelligence Optimizer for Diagnosing Oral Squamous Cell Carcinoma.

Cancer Diagnosis through Contour Visualization of Gene Expression Leveraging Deep Learning Techniques (2023)
Journal Article
Venkatesan, V. K., Kuppusamy Murugesan, K. R., Chandrasekaran, K. A., Thyluru Ramakrishna, M., Khan, S. B., Almusharraf, A., & Albuali, A. (in press). Cancer Diagnosis through Contour Visualization of Gene Expression Leveraging Deep Learning Techniques. Diagnostics, 13(22), 3452. https://doi.org/10.3390/diagnostics13223452

Prompt diagnostics and appropriate cancer therapy necessitate the use of gene expression databases. The integration of analytical methods can enhance detection precision by capturing intricate patterns and subtle connections in the data. This study p... Read More about Cancer Diagnosis through Contour Visualization of Gene Expression Leveraging Deep Learning Techniques.

Cloud-Based Quad Deep Ensemble Framework for the Detection of COVID-19 Omicron and Delta Variants (2023)
Journal Article
Tiwari, R. S., Dandabani, L., Das, T. K., Khan, S. B., Basheer, S., & Alqahtani, M. S. (in press). Cloud-Based Quad Deep Ensemble Framework for the Detection of COVID-19 Omicron and Delta Variants. Diagnostics, 13(22), 3419. https://doi.org/10.3390/diagnostics13223419

The mortality rates of patients contracting the Omicron and Delta variants of COVID-19 are very high, and COVID-19 is the worst variant of COVID. Hence, our objective is to detect COVID-19 Omicron and Delta variants from lung CT-scan images. We desig... Read More about Cloud-Based Quad Deep Ensemble Framework for the Detection of COVID-19 Omicron and Delta Variants.

An Alzheimer’s disease classification model using transfer learning densenet with embedded healthcare decision support system (2023)
Journal Article
Saleh, A. W., Gupta, G., Khan, S. B., Alkhaldi, N. A., & Verma, A. (2023). An Alzheimer’s disease classification model using transfer learning densenet with embedded healthcare decision support system. #Journal not on list, 9, 100348. https://doi.org/10.1016/j.dajour.2023.100348

Training a Convolutional Neural Network (CNN) from scratch is time-consuming and expensive. In this study, we propose implementing the DenseNet architecture for classification of AD in three classes. Our approach leverages transfer learning architect... Read More about An Alzheimer’s disease classification model using transfer learning densenet with embedded healthcare decision support system.

Critical Success Factors and Challenges in Adopting Digital Transformation in the Saudi Ministry of Education (2023)
Journal Article
Alojail, M., Alshehri, J., & Khan, S. B. (in press). Critical Success Factors and Challenges in Adopting Digital Transformation in the Saudi Ministry of Education. Sustainability, 15(21), 15492. https://doi.org/10.3390/su152115492

Many countries are using digital transformation to increase their productivity and organizational performance. In Saudi Arabia, digital transformation is a crucial part of their Saudi Vision 2030 plan, but it is still in its early stages. To understa... Read More about Critical Success Factors and Challenges in Adopting Digital Transformation in the Saudi Ministry of Education.

Managing Uncertainties in Supply Chains for Enhanced E-Commerce Engagement: A Generation Z Perspective on Retail Shopping through Facebook (2023)
Journal Article
Al Moteri, M., Alojail, M., & Khan, S. B. (in press). Managing Uncertainties in Supply Chains for Enhanced E-Commerce Engagement: A Generation Z Perspective on Retail Shopping through Facebook. Sustainability, 15(21), 15351. https://doi.org/10.3390/su152115351

This research investigates the uncertainties in supply chains using symmetrical and asymmetrical modeling tools, focusing on the attitudes of millennials towards Facebook retail shopping. By exploring antecedents such as pleasure, credibility, and pe... Read More about Managing Uncertainties in Supply Chains for Enhanced E-Commerce Engagement: A Generation Z Perspective on Retail Shopping through Facebook.

Optimizing Inference Distribution for Efficient Kidney Tumor Segmentation Using a UNet-PWP Deep-Learning Model with XAI on CT Scan Images (2023)
Journal Article
Rao, P. K., Chatterjee, S., Janardhan, M., Nagaraju, K., Khan, S. B., Almusharraf, A., & Alharbe, A. I. (in press). Optimizing Inference Distribution for Efficient Kidney Tumor Segmentation Using a UNet-PWP Deep-Learning Model with XAI on CT Scan Images. Diagnostics, 13(20), 3244. https://doi.org/10.3390/diagnostics13203244

Kidney tumors represent a significant medical challenge, characterized by their often-asymptomatic nature and the need for early detection to facilitate timely and effective intervention. Although neural networks have shown great promise in disease p... Read More about Optimizing Inference Distribution for Efficient Kidney Tumor Segmentation Using a UNet-PWP Deep-Learning Model with XAI on CT Scan Images.

Impact of Digital Transformation toward Sustainable Development (2023)
Journal Article
Alojail, M., & Khan, S. B. (in press). Impact of Digital Transformation toward Sustainable Development. Sustainability, 15(20), 14697. https://doi.org/10.3390/su152014697

The rapid advancements in digital technologies have prompted organizations to embrace digital transformations (DTs) in order to enhance efficiency, gain a competitive advantage, and achieve long-term sustainability objectives. However, the successful... Read More about Impact of Digital Transformation toward Sustainable Development.