The three-dimensional structure of a protein is determined by its amino acid sequence, and the function of the protein is highly dependent on its three-dimensional structure. The side-chain conformations of proteins play a crucial role in protein folding, protein-protein interactions, and de novo protein design. Accurate prediction of protein side-...
Sweat Fingerprint Identification Technology Based on Ion Dynamics: Research on Inkjet-Printed Organic Electrochemical Transistor Arrays Academic Background Sweat, as a non-invasive biomarker, contains rich physiological information that can reflect human health conditions, such as hydration balance and disease markers. However, sweat has complex co...
Introduction In recent years, solving partial differential equations (PDEs) using numerical methods has played a significant role in various fields such as engineering and medicine. These methods have shown remarkable effectiveness in applications like topology and design optimization as well as clinical prognostication. However, the high computati...
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...