Search Articles

Semantic Indexing of Medical Learning Objects: Medical Students' Usage of a Semantic Network

Nadine Tix, Paul Gießler, Ursula Ohnesorge-Radtke, Cord Spreckelsen

JMIR Med Educ 2015;1(2):e16

Download Citation: END BibTex RIS

Integration of Technology in Medical Education on Primary Care During the COVID-19 Pandemic: Students’ Viewpoint

Nadine Paul, Sae Kohara, Gursharan Kaur Khera, Ramith Gunawardena

JMIR Med Educ 2020;6(2):e22926

Download Citation: END BibTex RIS

Not Just a Medical Student: Delivering Medical Education Through a Short Video Series on Social Media

Nadine Abbas, Utkarsh Ojha

JMIR Med Educ 2019;5(1):e11971

Download Citation: END BibTex RIS

Consumer Participation in Quality Improvements for Chronic Disease Care: Development and Evaluation of an Interactive Patient-Centered Survey to Identify Preferred Service Initiatives

Elizabeth A Fradgley, Christine L Paul, Jamie Bryant, Ian A Roos, Frans A Henskens, David J Paul

J Med Internet Res 2014;16(12):e292

Download Citation: END BibTex RIS

#Healthy Selfies: Exploration of Health Topics on Instagram

Sachin Muralidhara, Michael J. Paul

JMIR Public Health Surveill 2018;4(2):e10150

Download Citation: END BibTex RIS

Identifying Protective Health Behaviors on Twitter: Observational Study of Travel Advisories and Zika Virus

Paul and Dredze similarly note that individuals often report medications used for symptom relief [4].As the largest known Zika outbreak occurred recently, researchers are only now beginning to investigate the use of internet data to understand this particular

Ashlynn R Daughton, Michael J Paul

J Med Internet Res 2019;21(5):e13090

Download Citation: END BibTex RIS

The Internet and Clinical Trials: Background, Online Resources, Examples and Issues

James Paul, Rachael Seib, Todd Prescott

J Med Internet Res 2005;7(1):e5

Download Citation: END BibTex RIS

Social Media as a Sensor of Air Quality and Public Response in China

Additionally, our entire dataset contains only 93 million messages, a much smaller dataset than those typically used in Twitter research today; for example, Paul and Dredze [3] used a general collection of 2 billion messages to study health topics on Twitter

Shiliang Wang, Michael J Paul, Mark Dredze

J Med Internet Res 2015;17(3):e22

Download Citation: END BibTex RIS

Comparison of Social Media, Syndromic Surveillance, and Microbiologic Acute Respiratory Infection Data: Observational Study

antihistaminesFor use in the analyses described in the following section, we extracted topics from all tweets using latent Dirichlet allocation (LDA) [29] and a Gibbs sampling implementation with automatic hyperparameter optimization described in the study by Paul

Ashlynn R Daughton, Rumi Chunara, Michael J Paul

JMIR Public Health Surveill 2020;6(2):e14986

Download Citation: END BibTex RIS

Virtual Reality Behavioral Activation as an Intervention for Major Depressive Disorder: Case Report

Margot Paul, Kim Bullock, Jeremy Bailenson

JMIR Ment Health 2020;7(11):e24331

Download Citation: END BibTex RIS