Fig 1.
The overview of ATEDRUG framework.
Table 1.
Dataset Description.
Table 2.
Aspect phrase with sentiment class.
Fig 2.
Distribution of sentiment proportion by disease conditions.
Fig 3.
Screenshot of Sample 1 and 2.
Table 3.
Performance evaluation of human-in-the-loop automated aspect term extraction.
Table 4.
Performance evaluation of human-in-the-loop automated polarity detection.
Table 5.
Performance Analysis of Deep Learning Models for Aspect Term Extraction and Polarity Detection.
Table 6.
G: Generated aspect terms and their polarity using Llama-2-7B; GM: Generated aspects terms and their polarity using Medalpaca-7b T: True aspect terms with polarity by human annotator.