130 citations · 215 across the 9 of their papers we have counts for
11 papers
Retrieving Evidence from EHRs with LLMs: Possibilities and Challenges
Hiba Ahsan, Denis Jered McInerney, Jisoo Kim +4
Unstructured data in Electronic Health Records (EHRs) often contains critical information -- complementary to imaging -- that could inform radiologists' diagnoses. But the large vo…
Revisiting Relation Extraction in the era of Large Language Models
Somin Wadhwa, Silvio Amir, Byron C. Wallace
Relation extraction (RE) is the core NLP task of inferring semantic relationships between entities from text. Standard supervised RE techniques entail training modules to tag token…
Jointly Extracting Interventions, Outcomes, and Findings from RCT Reports with LLMs
Somin Wadhwa, Jay DeYoung, Benjamin Nye +2
Results from Randomized Controlled Trials (RCTs) establish the comparative effectiveness of interventions, and are in turn critical inputs for evidence-based care. However, results…
RedHOT: A Corpus of Annotated Medical Questions, Experiences, and Claims on Social Media
Somin Wadhwa, Vivek Khetan, Silvio Amir +1
We present Reddit Health Online Talk (RedHOT), a corpus of 22,000 richly annotated social media posts from Reddit spanning 24 health conditions. Annotations include demarcations of…
On the Impact of Random Seeds on the Fairness of Clinical Classifiers
Silvio Amir, Jan-Willem van de Meent, Byron C. Wallace
Recent work has shown that fine-tuning large networks is surprisingly sensitive to changes in random seed(s). We explore the implications of this phenomenon for model fairness acro…
Demographic Representation and Collective Storytelling in the Me Too Twitter Hashtag Activism Movement
Aaron Mueller, Zach Wood-Doughty, Silvio Amir +2
The #MeToo movement on Twitter has drawn attention to the pervasive nature of sexual harassment and violence. While #MeToo has been praised for providing support for self-disclosur…
Quantifying Mental Health from Social Media with Neural User Embeddings
Silvio Amir, Glen Coppersmith, Paula Carvalho +2
Mental illnesses adversely affect a significant proportion of the population worldwide. However, the methods traditionally used for estimating and characterizing the prevalence of…
Expanding Subjective Lexicons for Social Media Mining with Embedding Subspaces
Silvio Amir, Rámon Astudillo, Wang Ling +2
Recent approaches for sentiment lexicon induction have capitalized on pre-trained word embeddings that capture latent semantic properties. However, embeddings obtained by optimizin…
Modelling Context with User Embeddings for Sarcasm Detection in Social Media
Silvio Amir, Byron C. Wallace, Hao Lyu +1
We introduce a deep neural network for automated sarcasm detection. Recent work has emphasized the need for models to capitalize on contextual features, beyond lexical and syntacti…
POPmine: Tracking Political Opinion on the Web
Pedro Saleiro, Sílvio Amir, Mário J. Silva +1
The automatic content analysis of mass media in the social sciences has become necessary and possible with the raise of social media and computational power. One particularly promi…
Finding Function in Form: Compositional Character Models for Open Vocabulary Word Representation
Wang Ling, Tiago Luís, Luís Marujo +5
We introduce a model for constructing vector representations of words by composing characters using bidirectional LSTMs. Relative to traditional word representation models that hav…