Outputs (315)

Arabic text classification based on analogical proportions (2024)
Journal Article
Bounhas, M., Elayeb, B., Chouigui, A., Hussain, A., & Cambria, E. (online). Arabic text classification based on analogical proportions. Expert Systems, https://doi.org/10.1111/exsy.13609

Text classification is the process of labelling a given set of text documents with predefined classes or categories. Existing Arabic text classifiers are either applying classic Machine Learning algorithms such as k-NN and SVM or using modern deep le... Read More about Arabic text classification based on analogical proportions.

Multi‐model deep learning system for screening human monkeypox using skin images (2024)
Journal Article
Gupta, K., Bajaj, V., Jain, D. K., & Hussain, A. (online). Multi‐model deep learning system for screening human monkeypox using skin images. Expert Systems, https://doi.org/10.1111/exsy.13651

Purpose Human monkeypox (MPX) is a viral infection that transmits between individuals via direct contact with animals, bodily fluids, respiratory droplets, and contaminated objects like bedding. Traditional manual screening for the MPX infection is... Read More about Multi‐model deep learning system for screening human monkeypox using skin images.

A Change Severity Degree-based Dynamic Multi-Objective Optimization Algorithm with Adaptive Response Strategy (2024)
Journal Article
Kouka, N., Fourati, R., Fdhila, R., Hussain, A., & Alimi, A. M. (2024). A Change Severity Degree-based Dynamic Multi-Objective Optimization Algorithm with Adaptive Response Strategy. Information Sciences, 677, Article 120794. https://doi.org/10.1016/j.ins.2024.120794

Many real-world optimization problems are dynamic by nature, exhibiting temporal variations in objective functions, constraints, and parameters. These problems present significant challenges for algorithm convergence and diversity,... Read More about A Change Severity Degree-based Dynamic Multi-Objective Optimization Algorithm with Adaptive Response Strategy.

Impact of the Covid-19 pandemic on audiology service delivery: Observational study of the role of social media in patient communication (2024)
Journal Article
Hussain, A., Hussain, Z., Gogate, M., Dashtipour, K., Ng, D., Riaz, M. S., Goman, A., Sheikh, A., & Hussain, A. (2024). Impact of the Covid-19 pandemic on audiology service delivery: Observational study of the role of social media in patient communication. PLOS ONE, 19(4), Article e0288223. https://doi.org/10.1371/journal.pone.0288223

The Covid-19 pandemic has highlighted an era in hearing health care that necessitates a comprehensive rethinking of audiology service delivery. There has been a significant increase in the number of individuals with hearing loss who seek information... Read More about Impact of the Covid-19 pandemic on audiology service delivery: Observational study of the role of social media in patient communication.

Graph learning with label attention and hyperbolic embedding for temporal event prediction in healthcare (2024)
Journal Article
Naseem, U., Thapa, S., Zhang, Q., Wang, S., Rashid, J., Hu, L., & Hussain, A. (2024). Graph learning with label attention and hyperbolic embedding for temporal event prediction in healthcare. Neurocomputing, 592, Article 127736. https://doi.org/10.1016/j.neucom.2024.127736

The digitization of healthcare systems has led to the proliferation of electronic health records (EHRs), serving as comprehensive repositories of patient information. However, the vast volume and complexity of EHR data present challenges in extractin... Read More about Graph learning with label attention and hyperbolic embedding for temporal event prediction in healthcare.

SAR Ship Instance Segmentation With Dynamic Key Points Information Enhancement (2024)
Journal Article
Gao, F., Han, X., Wang, J., Sun, J., Hussain, A., & Zhou, H. (2024). SAR Ship Instance Segmentation With Dynamic Key Points Information Enhancement. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17, 11365-11385. https://doi.org/10.1109/jstars.2024.3383779

There are several unresolved issues in the field of ship instance segmentation in synthetic aperture radar (SAR) images. First, in inshore dense ship area, the problems of missed detections and mask overlap frequently occur. Second, in inshore scenes... Read More about SAR Ship Instance Segmentation With Dynamic Key Points Information Enhancement.

Generative AI for Consumer Electronics: Enhancing User Experience with Cognitive and Semantic Computing (2024)
Journal Article
Chamola, V., Sai, S., Sai, R., Hussain, A., & Sikdar, B. (online). Generative AI for Consumer Electronics: Enhancing User Experience with Cognitive and Semantic Computing. IEEE Consumer Electronics Magazine, https://doi.org/10.1109/mce.2024.3387049

Generative Artificial Intelligence(GAI) models such as ChatGPT , DALL-E , and the recently introduced Gemini have attracted considerable interest in both business and academia because of their capacity to produce material in response to human inputs.... Read More about Generative AI for Consumer Electronics: Enhancing User Experience with Cognitive and Semantic Computing.

Overtaking Mechanisms Based on Augmented Intelligence for Autonomous Driving: Datasets, Methods, and Challenges (2024)
Journal Article
Chamola, V., Chougule, A., Sam, A., Hussain, A., & Yu, F. R. (2024). Overtaking Mechanisms Based on Augmented Intelligence for Autonomous Driving: Datasets, Methods, and Challenges. IEEE Internet of Things, 11(10), 17911-17933. https://doi.org/10.1109/jiot.2024.3362851

The field of autonomous driving research has made significant strides towards achieving full automation, endowing vehicles with self-awareness and independent decision-making. However, integrating automation into vehicular operations presents formida... Read More about Overtaking Mechanisms Based on Augmented Intelligence for Autonomous Driving: Datasets, Methods, and Challenges.

Can Generative AI Models Extract Deeper Sentiments as Compared to Traditional Deep Learning Algorithms? (2024)
Journal Article
Anas, M., Saiyeda, A., Sohail, S. S., Cambria, E., & Hussain, A. (2024). Can Generative AI Models Extract Deeper Sentiments as Compared to Traditional Deep Learning Algorithms?. IEEE Intelligent Systems, 39(2), 5-10. https://doi.org/10.1109/mis.2024.3374582

Recent advances in the context of deep learning have led to the development of generative artificial intelligence (AI) models which have shown remarkable performance in complex language understanding tasks. This study proposes an evaluation of tradit... Read More about Can Generative AI Models Extract Deeper Sentiments as Compared to Traditional Deep Learning Algorithms?.

Application of machine learning in predicting frailty syndrome in patients with heart failure (2024)
Journal Article
Szczepanowski, R., Uchmanowicz, I., Pasieczna-Dixit, A. H., Sobecki, J., Katarzyniak, R., Kołaczek, G., Lorkiewicz, W., Kędras, M., Dixit, A., Biegus, J., Wleklik, M., Gobbens, R. J., Hill, L., Jaarsma, T., Hussain, A., Barbagallo, M., Veronese, N., Morabito, F. C., & Kahsin, A. (2024). Application of machine learning in predicting frailty syndrome in patients with heart failure. Advances in Clinical and Experimental Medicine, 33(3), 309-315. https://doi.org/10.17219/acem/184040

Prevention and diagnosis of frailty syndrome (FS) in patients with heart failure (HF) require innovative systems to help medical personnel tailor and optimize their treatment and care. Traditional methods of diagnosing FS in patients could be more sa... Read More about Application of machine learning in predicting frailty syndrome in patients with heart failure.