F Abdullakutty, Y Akbari, S Al-Maadeed… - arXiv preprint arXiv …, 2024 - arxiv.org
It is imperative that breast cancer is detected precisely and timely to improve patient outcomes. Diagnostic methodologies have traditionally relied on unimodal approaches; …
AJ Fofanah, D Chen, L Wen, S Zhang - Expert Systems with Applications, 2024 - Elsevier
Significant challenges arise when Graph Neural Networks (GNNs) try to deal with uneven data. Specifically in signed and weighted graph structures. This makes classification tasks …
Breast cancer is a significant global health concern, with millions of cases and deaths each year. Accurate diagnosis is critical for timely treatment and medication. Machine learning …
D Shen, C Qin, Q Zhang, H Zhu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Recent years have witnessed the great success of the applications of graph convolutional networks (GCNs) in various scenarios. However, due to the challenging over-smoothing and …
W Ma, M Li, Z Chu, H Chen - Sensors, 2024 - mdpi.com
Biosensors play a crucial role in detecting cancer signals by orchestrating a series of intricate biological and physical transduction processes. Among various cancers, breast …
Gene therapy is an advanced medical approach that aims to find solutions for various cancers by identifying optimal gene expressions. In this context, computer-aided detection of …
Multi-omic data analysis incorporating machine learning has the potential to significantly improve cancer diagnosis and prognosis. Traditional machine learning methods are usually …
B Li, S Nabavi - Proceedings of the 14th ACM International Conference …, 2023 - dl.acm.org
Recent advancements in single-cell multiomics sequencing technology present new opportunities for researchers. However, the integrative analysis of the multiomics data poses …
B Li, S Nabavi - 2023 IEEE International Conference on …, 2023 - ieeexplore.ieee.org
Recent advancements in single-cell multiomics sequencing create new research opportunities but also pose challenges, particularly in cell clustering. One major challenge is …