10 citations · 27 across the 5 of their papers we have counts for
6 papers · 1 filter
Few-shot learning for medical text: A systematic review
Yao Ge, Yuting Guo, Yuan-Chi Yang +2
Objective: Few-shot learning (FSL) methods require small numbers of labeled instances for training. As many medical topics have limited annotated textual data in practical settings…
Towards Automatic Bot Detection in Twitter for Health-related Tasks
Anahita Davoudi, Ari Z. Klein, Abeed Sarker +1
With the increasing use of social media data for health-related research, the credibility of the information from this source has been questioned as the posts may originate from au…
Deep Neural Networks Ensemble for Detecting Medication Mentions in Tweets
Davy Weissenbacher, Abeed Sarker, Ari Klein +3
Objective: After years of research, Twitter posts are now recognized as an important source of patient-generated data, providing unique insights into population health. A fundament…
Automatically Detecting Self-Reported Birth Defect Outcomes on Twitter for Large-scale Epidemiological Research
Ari Z. Klein, Abeed Sarker, Davy Weissenbacher +1
In recent work, we identified and studied a small cohort of Twitter users whose pregnancies with birth defect outcomes could be observed via their publicly available tweets. Exploi…
Automated text summarisation and evidence-based medicine: A survey of two domains
Abeed Sarker, Diego Molla, Cecile Paris
The practice of evidence-based medicine (EBM) urges medical practitioners to utilise the latest research evidence when making clinical decisions. Because of the massive and growing…
Social media mining for identification and exploration of health-related information from pregnant women
Pramod Bharadwaj Chandrashekar, Arjun Magge, Abeed Sarker +1
Widespread use of social media has led to the generation of substantial amounts of information about individuals, including health-related information. Social media provides the op…