Objective In this systematic review, we aim to synthesize the literature on the use of natural
language processing (NLP) and text mining as they apply to symptom extraction and …

Breast cancer patients often experience symptoms that adversely affect their quality of life. It
is understood that many of these symptoms tend to cluster together: while they might have …

Background: Data representing people's behaviour, attitudes, feelings and relationships are
increasingly being harvested from social media platforms and re-used for research …

OBJECTIVES: To identify symptom clusters in breast cancer survivors and to determine
sociodemographic and clinical characteristics influencing symptom cluster membership …

Objective User-generated content (UGC) in online environments provides opportunities to
learn an individual's health status outside of clinical settings. However, the nature of UGC …

Background Social media platforms constitute a rich data source for natural language
processing tasks such as named entity recognition, relation extraction, and sentiment …

Patients with breast cancer experience treatment-related symptoms which are unlike side
effects associated with therapy such as surgery, chemotherapy or radiation. These …

Objective Seeing someone else experience side effects (ie, social modelling) can increase
negative expectations and subsequent nocebo effects. In face-to-face contexts, this effect …

Despite the application of advanced statistical and pharmacometric approaches to pediatric
trial data, a large pediatric evidence gap still remains. Here, we discuss how to collect more …

This study explores how breast cancer patients engage in travel and how travel may
improve patients' mental health. Data were collected from 31 breast cancer participants …