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SemEval-2022 Task 9: R2VQ – Competence-based Multimodal Question Answering
In this task, we identify a challenge that is reflective of linguistic and cognitive competencies that humans have when speaking and reasoning.
Dense Paraphrasing for Textual Enrichment
Understanding inferences and answering questions from text requires more than merely recovering surface arguments, adjuncts, or strings associated with the query terms.
Designing Multimodal Datasets for NLP Challenges
In this paper, we argue that the design and development of multimodal datasets for natural language processing (NLP) challenges should be enhanced in two significant respects: to more broadly represent commonsense semantic inferences; and to better reflect the dynamics of actions and events, through a substantive alignment of textual and visual information.
Assessing the Efficacy of Clinical Sentiment Analysis and Topic Extraction in Psychiatric Readmission Risk Prediction
Predicting which patients are more likely to be readmitted to a hospital within 30 days after discharge is a valuable piece of information in clinical decision-making.
Distinguishing Clinical Sentiment: The Importance of Domain Adaptation in Psychiatric Patient Health Records
In this study, we undertook, to our knowledge, the first domain adaptation of sentiment analysis to psychiatric EHRs by defining psychiatric clinical sentiment, performing an annotation project, and evaluating multiple sentence-level sentiment machine learning (ML) models.
Analysis of Risk Factor Domains in Psychosis Patient Health Records
Readmission after discharge from a hospital is disruptive and costly, regardless of the reason.
