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Found 10 papers, 2 papers with code
Pain Forecasting using Self-supervised Learning and Patient Phenotyping: An attempt to prevent Opioid Addiction
Opioids are often used to manage these painful episodes; the extent of their use in managing pain in this disorder is an issue of debate.
Exploring Language Patterns in a Medical Licensure Exam Item Bank
This study examines the use of natural language processing (NLP) models to evaluate whether language patterns used by item writers in a medical licensure exam might contain evidence of biased or stereotypical language.
Clustering of Pain Dynamics in Sickle Cell Disease from Sparse, Uneven Samples
Irregularly sampled time series data are common in a variety of fields.
Pain Intensity Assessment in Sickle Cell Disease patients using Vital Signs during Hospital Visits
Our experimental results demonstrate that ML techniques can provide an objective and quantitative evaluation of pain intensity levels for all three types of hospital visits.
COVID-19 and Mental Health/Substance Use Disorders on Reddit: A Longitudinal Study
This has been exacerbated by social isolation during the pandemic and the social stigma associated with mental health and substance use disorders, making people reluctant to share their struggles and seek help.
Predicting Early Indicators of Cognitive Decline from Verbal Utterances
Our experiments show that a combination of contextual and psycholinguistic features extracted by a Support Vector Machine improved distinguishing the verbal utterances of elderly controls, people with MCI, possible AD, and probable AD.
Topic-Centric Unsupervised Multi-Document Summarization of Scientific and News Articles
Recent advances in natural language processing have enabled automation of a wide range of tasks, including machine translation, named entity recognition, and sentiment analysis.
Leveraging Natural Language Processing to Mine Issues on Twitter During the COVID-19 Pandemic
In this study, we constructed a system to identify the relevant tweets related to the COVID-19 pandemic throughout January 1st, 2020 to April 30th, 2020, and explored topic modeling to identify the most discussed topics and themes during this period in our data set.
Clustering of Social Media Messages for Humanitarian Aid Response during Crisis
Social media has quickly grown into an essential tool for people to communicate and express their needs during crisis events.
Knowledge Graphs and Knowledge Networks: The Story in Brief
Knowledge Graphs (KGs) represent real-world noisy raw information in a structured form, capturing relationships between entities.
