KU_ED at SocialDisNER: Extracting Disease Mentions in Tweets Written in Spanish
This paper describes our system developed for the Social Media Mining for Health (SMM4H) 2022 SocialDisNER task. We used several types of pre-trained language models, which are trained on Spanish biomedical literature or Spanish Tweets. We showed the difference in performance depending on the quality of the tokenization as well as introducing silver standard annotations when training the model. Our model obtained a strict F1 of 80.3% on the test set, which is an improvement of +12.8% F1 (24.6 std) over the average results across all submissions to the SocialDisNER challenge.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
NLP-CIC-WFU at SocialDisNER: Disease Mention Extraction in Spanish Tweets Using Transfer Learning and Search by Propagation
Named entity recognition (e.g., disease mention extraction) is one of the most relevant tasks for data mining in the medical field. Although it is a well-known challenge, the bulk of the efforts to tackle this task have …
named-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)Transfer LearningPLN CMM at SocialDisNER: Improving Detection of Disease Mentions in Tweets by Using Document-Level Features
This paper describes our approaches used to solve the SocialDisNER task, which belongs to the Social Media Mining for Health Applications (SMM4H) shared task. This task aims to identify disease mentions in tweets written…
Language ModelingLanguage ModellingSentenceThe SocialDisNER shared task on detection of disease mentions in health-relevant content from social media: methods, evaluation, guidelines and corpora
There is a pressing need to exploit health-related content from social media, a global source of data where key health information is posted directly by citizens, patients and other healthcare stakeholders. Use cases of …
Knowledge GraphsPharmacovigilanceIAI @ SocialDisNER : Catch me if you can! Capturing complex disease mentions in tweets
Biomedical NER is an active research area today. Despite the availability of state-of-the-art models for standard NER tasks, their performance degrades on biomedical data due to OOV entities and the challenges encountere…
NERdezzai@SMM4H’22: Tasks 5 & 10 - Hybrid models everywhere
This paper presents our approaches to SMM4H’22 task 5 - Classification of tweets of self-reported COVID-19 symptoms in Spanish, and task 10 - Detection of disease mentions in tweets – SocialDisNER (in Spanish). We have p…