Graph representation learning in biomedicine and healthcare
Networks—or graphs—are universal descriptors of systems of interacting elements. In
biomedicine and healthcare, they can represent, for example, molecular interactions …
biomedicine and healthcare, they can represent, for example, molecular interactions …
Machine learning for lung cancer diagnosis, treatment, and prognosis
The recent development of imaging and sequencing technologies enables systematic
advances in the clinical study of lung cancer. Meanwhile, the human mind is limited in …
advances in the clinical study of lung cancer. Meanwhile, the human mind is limited in …
GDroid: Android malware detection and classification with graph convolutional network
The dramatic increase in the number of malware poses a serious challenge to the Android
platform and makes it difficult for malware analysis. In this paper, we propose a novel …
platform and makes it difficult for malware analysis. In this paper, we propose a novel …
Trustworthy multi-phase liver tumor segmentation via evidence-based uncertainty
C Hu, T ** an artificial intelligence system that can automatically make lab …
AX-Unet: A deep learning framework for image segmentation to assist pancreatic tumor diagnosis
Image segmentation plays an essential role in medical imaging analysis such as tumor
boundary extraction. Recently, deep learning techniques have dramatically improved …
boundary extraction. Recently, deep learning techniques have dramatically improved …