Large language models in mental health care: a scoping review
Objective: The growing use of large language models (LLMs) stimulates a need for a
comprehensive review of their applications and outcomes in mental health care contexts …
comprehensive review of their applications and outcomes in mental health care contexts …
Monkeypox2022tweets: a large-scale twitter dataset on the 2022 monkeypox outbreak, findings from analysis of tweets, and open research questions
N Thakur - Infectious Disease Reports, 2022 - mdpi.com
The mining of Tweets to develop datasets on recent issues, global challenges, pandemics,
virus outbreaks, emerging technologies, and trending matters has been of significant interest …
virus outbreaks, emerging technologies, and trending matters has been of significant interest …
A deep learning approach for transgender and gender diverse patient identification in electronic health records
Background Although accurate identification of gender identity in the electronic health
record (EHR) is crucial for providing equitable health care, particularly for transgender and …
record (EHR) is crucial for providing equitable health care, particularly for transgender and …
[HTML][HTML] Tracking the impact of COVID-19 and lockdown policies on public mental health using social media: infoveillance study
Background The COVID-19 pandemic and its corresponding preventive and control
measures have increased the mental burden on the public. Understanding and tracking …
measures have increased the mental burden on the public. Understanding and tracking …
Patient safety discourse in a pandemic: a Twitter hashtag analysis study on# PatientSafety
O Litvinova, FB Matin, M Matin… - Frontiers in public …, 2023 - frontiersin.org
Background The digitalization of medicine is becoming a transformative force in modern
healthcare systems. This study aims to investigate discussions regarding patient safety, as …
healthcare systems. This study aims to investigate discussions regarding patient safety, as …
[HTML][HTML] Trend and co-occurrence network of COVID-19 symptoms from large-scale social media data: infoveillance study
Background For an emergent pandemic, such as COVID-19, the statistics of symptoms
based on hospital data may be biased or delayed due to the high proportion of …
based on hospital data may be biased or delayed due to the high proportion of …
Mets-cov: A dataset of medical entity and targeted sentiment on covid-19 related tweets
The COVID-19 pandemic continues to bring up various topics discussed or debated on
social media. In order to explore the impact of pandemics on people's lives, it is crucial to …
social media. In order to explore the impact of pandemics on people's lives, it is crucial to …
Off-label drug use during the COVID-19 pandemic in Africa: topic modelling and sentiment analysis of ivermectin in South Africa and Nigeria as a case study
Z Movahedi Nia, NL Bragazzi… - Journal of the …, 2023 - royalsocietypublishing.org
Although rejected by the World Health Organization, the human and even veterinary
formulation of ivermectin has widely been used for prevention and treatment of COVID-19. In …
formulation of ivermectin has widely been used for prevention and treatment of COVID-19. In …
Dissemination of Registered COVID-19 Clinical Trials (DIRECCT): a cross-sectional study
M Salholz-Hillel, M Pugh-Jones, N Hildebrand… - BMC medicine, 2023 - Springer
Background The results of clinical trials should be completely and rapidly reported during
public health emergencies such as COVID-19. This study aimed to examine when, and …
public health emergencies such as COVID-19. This study aimed to examine when, and …
Streamlining social media information retrieval for public health research with deep learning
Objective Social media-based public health research is crucial for epidemic surveillance, but
most studies identify relevant corpora with keyword-matching. This study develops a system …
most studies identify relevant corpora with keyword-matching. This study develops a system …