most citedAccurate Medical Named Entity Recognition Through Specialized NLP Models

1 citations · 4 across the 5 of their papers we have counts for

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5 papers

cs.CL20241 cited

Accurate Medical Named Entity Recognition Through Specialized NLP Models

Jiacheng Hu, Runyuan Bao, Yang Lin +2

This study evaluated the effect of BioBERT in medical text processing for the task of medical named entity recognition. Through comparative experiments with models such as BERT, Cl…

eess.IV20241 cited

Enhancing Medical Image Segmentation with Deep Learning and Diffusion Models

Houze Liu, Tong Zhou, Yanlin Xiang +3

Medical image segmentation is crucial for accurate clinical diagnoses, yet it faces challenges such as low contrast between lesions and normal tissues, unclear boundaries, and high…

cs.CV20241 cited

Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data

Aoran Shen, Minghao Dai, Jiacheng Hu +3

In the 21st-century information age, with the development of big data technology, effectively extracting valuable information from massive data has become a key issue. Traditional…

eess.IV20241 cited

Deep Learning with HM-VGG: AI Strategies for Multi-modal Image Analysis

Junliang Du, Yiru Cang, Tong Zhou +2

This study introduces the Hybrid Multi-modal VGG (HM-VGG) model, a cutting-edge deep learning approach for the early diagnosis of glaucoma. The HM-VGG model utilizes an attention m…

cs.CL2024

Deep Learning for Medical Text Processing: BERT Model Fine-Tuning and Comparative Study

Jiacheng Hu, Yiru Cang, Guiran Liu +3

This paper proposes a medical literature summary generation method based on the BERT model to address the challenges brought by the current explosion of medical information. By fin…