Publications by authors named "Zi-Neng Yan"
Artificial intelligence (AI) is an interdisciplinary field that combines computer technology, mathematics, and several other fields. Recently, with the rapid development of machine learning (ML) and deep learning (DL), significant progress has been made in the field of AI. As one of the fastest-growing branches, DL can effectively extract features from big data and optimize the performance of various tasks.
View Article and Find Full Text PDFObjective: To evaluate the accuracy and parsing ability of GPT 4.0 for Japanese medical practitioner qualification examinations in a multidimensional way to investigate its response accuracy and comprehensiveness to medical knowledge.
Methods: We evaluated the performance of the GPT 4.
Article Synopsis
- This study compared the effectiveness of optimized vs. unoptimized large language models (LLMs) in answering orthopedic questions using a specialized knowledge base.
- A knowledge base was created using clinical guidelines and authoritative publications, and 30 orthopedic questions were posed to both types of LLMs, with responses evaluated by experienced orthopedic surgeons.
- Results indicated that optimization led to significant improvements across all models in quality, accuracy, and comprehensiveness, suggesting that tailored knowledge bases can enhance LLM performance in specialized fields.
Article Synopsis
- The brain-computer interface (BCI) system connects external devices to the human brain and reflects mental states through EEG signals, which can often be contaminated by various artifacts.
- The complexity of unprocessed EEG data makes analysis and cleanup difficult, posing challenges for accurate readings.
- Recent advancements in artificial intelligence (AI) and machine learning have significantly improved the processing of EEG signals, allowing for better understanding of patients' health and potentially enhancing their quality of life.