Yizhou Yu

An open AI system for dermatology tasks

Hong-Yu Zhou, Linwei Chen, Lijun Liu, Ying Fu et autres

cn, hk (code pays fourni par la source)

NavGemini: a multi-modal LLM agent for vision-and-language navigation

Ganlong Zhao, GuanBin Li, Yizhou Yu

Abstract Large language models (LLMs) such as the GPT series exhibit impressive reasoning and in-context learning capabilities due to the substantial amount of data and computational resources involved in LLM training. Some previous studies have applied the LLMs to vision-and-language navigation (VLN) …

hk, cn (code pays fourni par la source)

Design of a simulation system for coherent and envelope demodulation based on LabVIEW

Yizhou Yu

cn (code pays fourni par la source)

Latent Diffusion With Topology-Preserving Conditioning for Structure-Aware Data Generation

Qin Lei, C.-H Chen, Jiang Zhong, Xin Xiao et autres

Conditional latent diffusion has become a promising paradigm for synthesizing paired image-mask data for segmentation, yet preserving structural topology remains challenging for curvilinear objects such as vessels and cracks. Existing methods mainly focus on how to inject spatial conditions into generative backbones, …

cn, hk (code pays fourni par la source)

Deep Learning for Coronary Stenosis Detection in Heavily Calcified Plaques at Coronary CT Angiography: A Stepwise, Multicenter Study

Rui Wang, Libo Zhang, Uwe Joseph Schoepf, Fandong Zhang et autres

The proposed deep learning model automatically quantified coronary luminal stenosis in patients with heavily calcified plaques at coronary CT angiography and improved radiologists’ diagnostic performance.

cn, au, us, hk (code pays fourni par la source)

Visualizing Radiologic Connections: An Explainable Coarse-to-Fine Foundation Model with Multiview Mammograms and Associated Reports

Yuan Gao, Hong-Yu Zhou, Xin Wang, Antonio Portaluri et autres

The proposed explainable pretraining framework for multiview mammograms and associated reports demonstrated high label efficiency in malignancy recognition, segmentation, and localization across four external public datasets.

nl, us, cn, it, de, hk, mo (code pays fourni par la source)

A large language model for clinical outcome adjudication from telephone follow-up interviews: a secondary analysis of a multicenter randomized clinical trial

Zhao Shi, Bingqian Wu, Bin Hu, Jian Zhong et autres

Automated adjudication of clinical outcomes from telephone follow-ups is crucial for reducing workload and increasing data quality in large-scale trials. Here, we show that a domain-specific large language model (Fu-LLM) effectively automates the preadjudication of key clinical events-including death, hospitalization, and medication …

cn, us, hk (code pays fourni par la source)

Rethinking Discrete Tokens: Treating Them as Conditions for Continuous Autoregressive Image Synthesis

Peng Zheng, Junke Wang, Yi Chang, Yizhou Yu et autres

Recent advances in large language models (LLMs) have spurred interests in encoding images as discrete tokens and leveraging autoregressive (AR) frameworks for visual generation. However, the quantization process in AR-based visual generation models inherently introduces information loss that degrades image fidelity. To …

cn (code pays fourni par la source)

ScreenLungNet: Personalized Long-Term Prediction of Lung Cancer Risk from a Single Low-Dose CT Screening

Chu-Ti Lin, Weixiong Tan, Z.‐G. Zhou, Lingying Zhu et autres

The ScreenLungNet model, integrating multiple nodules and global lung features from low-dose CT, outperformed single-feature models in long-term lung cancer risk prediction, and enabled prediction even in screening-negative participants.

cn, hk (code pays fourni par la source)

Integrating Compressed Sensing with Radiomics Feature Selection for Outcome Prediction in Pulsar

Yizhou Yu, Hui Ying Peng

A2Mamba: Attention-augmented State Space Models for Visual Recognition

Meng Lou, Yunxiang Fu, Yizhou Yu

Transformers and Mamba, initially invented for natural language processing, have inspired backbone architectures for visual recognition. Recent studies integrated Local Attention Transformers with Mamba to capture both local details and global contexts. Despite competitive performance, these methods are limited to simple stacking …

VLN-R1: Vision-Language Navigation via Reinforcement Fine-Tuning

Zhangyang Qi, Zhixiong Zhang, Yizhou Yu, Jiaqi Wang et autres

Vision-Language Navigation (VLN) is a core challenge in embodied AI, requiring agents to navigate real-world environments using natural language instructions. Current language model-based navigation systems operate on discrete topological graphs, limiting path planning to predefined node connections. We propose VLN-R1, an end-to-end …