Skip to content
Log in
Sponsored AI AM CLAUDE, A Beginner's Guide: Learn the basics of working with AI AI AM CLAUDE, A Beginner's Guide: Learn the basics of working with AI

Author

Suhaila Abuowaida

h-index 18 View on Semantic Scholar

We have 4 of 71 papers

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Open access Sep 2026

Explainable machine learning for leukaemia diagnosis: enhancing interpretability and trust

By bridging the gap between computational accuracy and clinical reliability, XAI ensures that ML models can be safely integrated into diagnostic workflows and strengthen confidence in AI-driven leukaemia diagnosis, supporting more informed medical decisions and improving patient care.

Hamza Abu Owida, Mohammad R. Hassan, Nidal M. Turab et al. · 0 citations
Open access 2026

Deep ANN feature fusion with multi-stage data processing and visualization for enhanced breast cancer detection in ultrasound images

This paper proposes a new dynamic feature fusion technique called adaptive gated cross attention fusion (AGCAF), which utilizes a learnable gating function and two-way cross attention to dynamically weight each contribution of features from the DeIT and ViT backbones.

S. Abuowaida, H. Owida, H. Mashagba et al. · 0 citations
Open access Jul 2026

TRT-GLA: Tri-Representation Transformers with Global-Local Attention for High-Fidelity Multi-Modal MRI Super-Resolution

A Tri-Representation hybrid framework for MRI SR, TRT-GLA is proposed that redefines the MRI SR task as a joint spatial–spectral–structural high-resolution image generation problem, and establishes the utility of TRT-GLA in supporting quantitative analysis through a downstream tumor segmentation experiment that is clin...

Suhaila Abuowaida, H. Owida, T. Hamadneh et al. · 0 citations
Open access Aug 2026

Artificial intelligence model: optimizing cancer risk level predictions using machine learning and deep learning approaches

The RF model’s ability to effectively estimate cancer risk levels among individuals, allowing for earlier discovery and more effective medical care is demonstrated, resulting in reliable generalization and accuracy estimates.

Areen M. Arabiat, H. Owida, Suhaila Abuowaida et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.