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Found 26 papers, 4 papers with code
Human-Human Health Coaching via Text Messages: Corpus, Annotation, and Analysis
In this paper, we discuss these schemas and briefly talk about their application for automatically extracting activity goals and annotating the second round of data, collected with different health coaches and patients.
A New Public Corpus for Clinical Section Identification: MedSecId
The process by which sections in a document are demarcated and labeled is known as section identification.
Summarizing Behavioral Change Goals from SMS Exchanges to Support Health Coaches
In this paper, we present our work towards assisting health coaches by extracting the physical activity goal the user and coach negotiate via text messages.
Modeling Low-Resource Health Coaching Dialogues via Neuro-Symbolic Goal Summarization and Text-Units-Text Generation
Health coaching helps patients achieve personalized and lifestyle-related goals, effectively managing chronic conditions and alleviating mental health issues.
Towards Enhancing Health Coaching Dialogue in Low-Resource Settings
In this paper, we propose to build a dialogue system that converses with the patients, helps them create and accomplish specific goals, and can address their emotions with empathy.
A Neuro-Symbolic Approach to Monitoring Salt Content in Food
We propose a dialogue system that enables heart failure patients to inquire about salt content in foods and help them monitor and reduce salt intake.
Reference Resolution and Context Change in Multimodal Situated Dialogue for Exploring Data Visualizations
Our focus is on resolving references to visualizations on a large screen display in multimodal dialogue; crucially, reference resolution is directly involved in the process of creating new visualizations.
DeepZensols: Deep Natural Language Processing Framework
Reproducing results in publications by distributing publicly available source code is becoming ever more popular.
Heart Failure Education of African American and Hispanic/Latino Patients: Data Collection and Analysis
People with heart failure need to actively participate in home self-care regimens to maintain good health.
Detecting and understanding moral biases in news
We describe work in progress on detecting and understanding the moral biases of news sources by combining framing theory with natural language processing.
A Corpus for Visual Question Answering Annotated with Frame Semantic Information
Visual Question Answering (VQA) has been widely explored as a computer vision problem, however enhancing VQA systems with linguistic information is necessary for tackling the complexity of the task.
Augmenting Small Data to Classify Contextualized Dialogue Acts for Exploratory Visualization
Our goal is to develop an intelligent assistant to support users explore data via visualizations.
Augmenting Visual Question Answering with Semantic Frame Information in a Multitask Learning Approach
Our first contribution is a new VQA dataset (imSituVQA) that we built by taking advantage of the imSitu annotations.
A Quantitative Analysis of Patients' Narratives of Heart Failure
Patients with chronic conditions like heart failure are the most likely to be re-hospitalized.
A Supervised Approach To The Interpretation Of Imperative To-Do Lists
To-do lists are a popular medium for personal information management.
Towards Generating Personalized Hospitalization Summaries
Most of the health documents, including patient education materials and discharge notes, are usually flooded with medical jargons and contain a lot of generic information about the health issue.
An effective Discourse Parser that uses Rich Linguistic Information
This paper presents a first-order logic learning approach to determine rhetorical relations between discourse segments.
