Papers by Pardis Ranjbar-Noiey

2 papers
Identifying Medical Self-Disclosure in Online Communities (2021.naacl-main)

Copied to clipboard

Challenge: a new dataset of health-related posts from online social platforms is available for analysis . medical self-disclosure may be useful for early detection and treatment of medical issues .
Approach: They propose to analyze medical self-disclosure in online health conversations . they release a dataset of health-related posts from online social platforms with high inter-annotator agreement .
Outcome: The proposed model achieves an accuracy of 81.02% and sets a strong performance benchmark.
What Clued the AI Doctor In? On the Influence of Data Source and Quality for Transformer-Based Medical Self-Disclosure Detection (2023.eacl-main)

Copied to clipboard

Challenge: Recognizing medical self-disclosure is important in many healthcare contexts, but it has been under-explored by the NLP community.
Approach: They analyze a social media-based task to expand existing medical self-disclosure corpus and compare Transformer-based models to determine their merits.
Outcome: The proposed dataset outperforms the state-of-the-art dataset for this task by 16.73%.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations