Organoids, miniature and simplified in vitro model systems that mimic the structure and
function of organs, have attracted considerable interest due to their promising applications in …

Research into the potential benefits of artificial intelligence for comprehending the intricate
biology of cancer has grown as a result of the widespread use of deep learning and …

Intelligent diagnosis processes rely on Artificial Intelligence (AI) techniques to provide
possible diagnoses by analyzing patient data and medical information. To make accurate …

Breast cancer is a significant global health burden, with increasing morbidity and mortality
worldwide. Early screening and accurate diagnosis are crucial for improving prognosis …

Albeit the notable performance on in-domain test points, it is non-trivial for deep neural
networks to attain satisfactory accuracy when deploying in the open world, where novel …

Cancer of unknown primary (CUP) site poses diagnostic challenges due to its elusive
nature. Many cases of CUP manifest as pleural and peritoneal serous effusions. Leveraging …

The field of oncology has witnessed an extraordinary surge in the application of big data and
artificial intelligence (AI). AI development has made multiscale and multimodal data fusion …

Compared to unsupervised domain adaptation, semi-supervised domain adaptation (SSDA)
aims to significantly improve the classification performance and generalization capability of …

The generalization capability of machine learning systems degenerates notably when the
test distribution drifts from the training distribution. Recently, Domain Generalization (DG) …

In a first study, this paper argues and demonstrates that spiking neural networks (SNN) can
be successfully used for predictive and explainable modelling of multimodal streaming data …