Shandong Institute of Automation

ProtoSurv: prototype-guided adaptation of computed tomography foundation model for lung-cancer prognosis prediction

Abstract Prognosis prediction is important for precision treatment in lung cancer. Chest computed tomography (CT) and deep learning are feasible approaches for learning imaging-based prognostic representations. However, prognostic labels are difficult to obtain because survival e...

RL-accelerated OSQP for real-time asymmetric corotational beam contact simulation in continuum robots

The real-time simulation of highly deformable slender structures interacting with complex, irregular boundaries remains a computationally demanding challenge in computational mechanics. A prominent motivating application for this fundamental problem is the navigation of continuum...

Vision-language sample scoring with dynamic coverage-centric strategies

Data pruning reduces image-classifier training cost by replacing a full training set with a coreset. Existing methods often require training a target or proxy model to estimate sample importance, which ties data selection to a particular architecture. In addition, common allocati...

A multimodal deep learning method based on multiple medical images for Fuchs endothelial corneal dystrophy diagnosis

To establish a multimodal deep learning network for the automated diagnosis of Fuchs endothelial corneal dystrophy (FECD). The ResNet-50 neural network was trained and validated using patients with FECD, patients with other corneal endothelial disorders, and healthy controls. At...

NB-Net: A Biologically-Inspired Framework for Neural Network Width Expansion

Abstract Deep learning has achieved remarkable success across various fields, however, most research in this area has primarily focused on increasing network depth, leading to a relative lack of systematic exploration of network width. Inspired by the structure of biological neur...

Computational Oncology of Chemotaxis-Driven Tumour–Immune Spatial Patterning and Stability

We develop a reaction–diffusion–chemotaxis model for spatial tumour–immune–chemokine dynamics that couples logistic tumour growth, immune-mediated killing, chemokine-dependent immune recruitment, chemotactic migration, and signal production. For the non-dimensional system, we est...