Leveraging Large Language Models for Accurate Extraction of Acupuncture Point Locations and Spatial Relationships
Large language models, particularly fine-tuned GPT-3.5, demonstrate superior performance in extracting complex spatial relationships between acupuncture points and human anatomy compared to traditional deep learning models.
High-throughput Biomedical Relation Extraction with Large Language Models
Developing a high-throughput biomedical relation extraction system using large language models for semi-structured web articles.
Extracting Biomedical Entities from Noisy Audio Transcripts: Bridging the ASR-NLP Gap
Addressing the challenges of noisy audio in biomedical NER tasks through innovative dataset creation and GPT4-based transcript cleaning.
Accurate and Interpretable Drug-Drug Interaction Prediction Enabled by Knowledge Subgraph Learning
KnowDDI combines rich biomedical knowledge with deep learning techniques to predict drug-drug interactions accurately and interpretably.
Pipelined Biomedical Event Extraction with N-ary Relation Extraction for Binding Events
N-ary relation extraction improves performance of Binding events in pipelined biomedical event extraction.
Spatial-aware Transformer-GRU Framework for Enhanced Glaucoma Diagnosis from 3D OCT Imaging
The author presents a novel deep learning framework that combines a Vision Transformer and a bidirectional GRU to enhance glaucoma diagnosis accuracy using 3D OCT imaging.
Dual-stage Optimizer for Overestimation Adjustment in Multi-Objective Genetic Algorithms for Biomarker Selection
The author proposes DOSA-MO, a novel multi-objective optimization wrapper algorithm that adjusts performance expectations during optimization to improve model selection and reduce overestimation.
