Explainable artificial intelligence: A survey of needs, techniques, applications, and future direction
Artificial intelligence models encounter significant challenges due to their black-box nature,
particularly in safety-critical domains such as healthcare, finance, and autonomous vehicles …
particularly in safety-critical domains such as healthcare, finance, and autonomous vehicles …
An enhanced hyper-parameter optimization of a convolutional neural network model for leukemia cancer diagnosis in a smart healthcare system
Healthcare systems in recent times have witnessed timely diagnoses with a high level of
accuracy. Internet of Medical Things (IoMT)-enabled deep learning (DL) models have been …
accuracy. Internet of Medical Things (IoMT)-enabled deep learning (DL) models have been …
Explainable artificial intelligence (XAI) in medical decision support systems (MDSS): applicability, prospects, legal implications, and challenges
The healthcare sector is very interested in machine learning (ML) and artificial intelligence
(AI). Nevertheless, applying AI applications in scientific contexts is difficult because of the …
(AI). Nevertheless, applying AI applications in scientific contexts is difficult because of the …
Explainable Machine Learning (XML) for Multimedia-Based Healthcare Systems: Opportunities, Challenges, Ethical and Future Prospects
Various scientific fields have abruptly shifted in the direction of data-dependent
methodologies in recent years. In some instances, concurrent improvements in data …
methodologies in recent years. In some instances, concurrent improvements in data …
Explainable artificial intelligence with scaling techniques to classify breast cancer images
Abstract According to the Breast Cancer Institute, one of the most hazardous diseases for
women is breast cancer (BCI). Clinical specialists claim that detecting this malignancy early …
women is breast cancer (BCI). Clinical specialists claim that detecting this malignancy early …
An enhanced residual networks based framework for early alzheimer's disease classification and diagnosis
Alzheimer's disease (AD) is a long-lasting, degenerative brain illness for which there is now
no successful treatment. However, there are medications that can delay its growth and stop …
no successful treatment. However, there are medications that can delay its growth and stop …
[PDF][PDF] Artificial intelligence-enabled security systems for 6G wireless networks: algorithms, strategies, and applications
With incredibly complex and diverse requirements, 6G is anticipated to support the
extraordinary Internet of Things advances. To effectively satisfy a wide range of …
extraordinary Internet of Things advances. To effectively satisfy a wide range of …
Brain Tumor Detection and Segmentation Using Deep Learning Models
This study focuses on brain tumor detection and segmentation using Convolutional Neural
Networks (CNN) with architectures of Fully Convolutional Net-work (FCN) and VGG16. The …
Networks (CNN) with architectures of Fully Convolutional Net-work (FCN) and VGG16. The …
Word sense disambiguation in biomedical applications
JB Awotunde - Mining Biomedical Text, Images and Visual Features …, 2025 - Elsevier
Word sense disambiguation (WSD) in biomedical applications plays an important role in the
advancement of natural language processing (NLP) capabilities, specifically in the domain …
advancement of natural language processing (NLP) capabilities, specifically in the domain …
Artificial Intelligence in Industry 5.0: Transforming Manufacturing through Machine Learning and Robotics in Collaborative Age
B Priya, V Sharma, JB Awotunde… - … Intelligence in Industry 4.0 … - taylorfrancis.com
Industry 5.0 is revolutionizing the manufacturing industry by enabling the integration of
advanced technologies such as artificial intelligence (AI), machine learning (ML), and …
advanced technologies such as artificial intelligence (AI), machine learning (ML), and …