The Application of Large Language Models in PET Imaging Reports: A Single-Center Pilot Study Combining Retrieval-Augmented Generation With the rapid development of artificial intelligence, large language models (LLMs) have gained widespread attention for their zero-shot learning and natural language processing capabilities in the medical domain. Al...
Application of AI-Enhanced Ultra-Fast PSMA-PET in Prostate Cancer Staging Academic Background Prostate cancer is one of the most common cancers among men globally, and accurate diagnosis and staging are crucial for treatment decision-making. Prostate-specific membrane antigen (PSMA) positron emission tomography (PET) has become a standard examinati...
Neural Network-Powered Microsurgical System: Advancing Precision in Cataract Surgery Academic Context and Research Problem Cataracts are the leading cause of blindness worldwide. Phacoemulsification combined with intraocular lens (IOL) implantation has emerged as the primary treatment method. This approach not only significantly improves patients’ ...
Unified Large Language Models and Knowledge Graphs Background In recent years, numerous research achievements have emerged in the fields of natural language processing and artificial intelligence. Notably, large language models (LLMs) such as ChatGPT and GPT-4 have demonstrated remarkable performance. However, despite their excellent generalization...
Knowledge Graph (KG) embedding technology is an important research topic in the field of artificial intelligence, mainly used for knowledge acquisition and extension of knowledge graphs. In recent years, although many graph embedding methods have been proposed, these methods typically focus only on the semantic information of the knowledge graph, i...
Multi-center Study on Artificial Intelligence-based Classification of Breast Lesions In the field of breast cancer, early diagnosis is crucial for improving treatment efficacy and survival rate. Breast cancer can be mainly divided into two categories: in situ carcinoma and invasive carcinoma, which have significant differences in treatment strategi...
Application of Radiomics in Predicting Local Control in Postoperative Stereotactic Radiotherapy for Brain Metastasis Patients Academic Background Brain Metastases (BMs) are the most common malignant brain tumors, far surpassing primary brain tumors like gliomas in incidence. Recent medical guidelines recommend surgical treatment for patients with s...
Automated Spinal Cord Segmentation Pipeline Based on Convolutional Neural Network (CNN) for Individualized Cat Spinal Cord Stimulation Modeling Background and Research Motivation Spinal cord stimulation (SCS) is a widely used treatment method for chronic pain management. In recent years, it has also been used to modulate neural activity, aiming to ...
StrokeClassifier: An AI Tool for Etiological Classification of Ischemic Stroke Based on Electronic Health Records Project Background and Motivation Identifying the etiology of strokes, particularly acute ischemic stroke (AIS), is crucial for secondary prevention, but it is often very challenging. In the United States, there are nearly 676,000 new c...