User Experience of Symptom Checkers: A Systematic Review.

This review reports the user experience of symptom checkers, aiming to characterize users studied in the existing literature, identify the aspects of user experience of symptom checkers that have been studied, and offer design suggestions. Our literature search resulted in 31 publications. We found that (1) most symptom checker users are relatively young; (2) eight relevant aspects of user experience have been explored, including motivation, trust, acceptability, satisfaction, accuracy, usability, safety/security, and functionality; (3) future symptom checkers should improve their accuracy, safety, and usability.

AutoMed: Automated Medical Risk Predictive Modeling on Electronic Health Records.

Electronic health records (EHR) have been widely applied to various tasks in the medical domain such as risk predictive modeling, which aims to predict further health conditions by analyzing patients' historical EHR. Existing work mainly focuses on modeling the sequential and temporal characteristics of EHR data with advanced deep learning techniques. However, the network architectures of these models are all manually designed based on experts' prior knowledge, which largely impedes non-experts from exploring this task.

Self-Diagnosis through AI-enabled Chatbot-based Symptom Checkers: User Experiences and Design Considerations.

Recently, there has been a growing interest in developing AI-enabled chatbot-based symptom checker (CSC) apps in the healthcare market. CSC apps provide potential diagnoses for users and assist them with self-triaging based on Artificial Intelligence (AI) techniques using human-like conversations. Despite the popularity of such CSC apps, little research has been done to investigate their functionalities and user experiences.

Physician champions' perspectives and practices on electronic health records implementation: challenges and strategies.

Objective: Physician champions are "boots on the ground" physician leaders who facilitate the implementation of, and transition to, new health information technology (HIT) systems within an organization. They are commonly cited as key personnel in HIT implementations, yet little research has focused on their practices and perspectives.

Materials And Methods: We addressed this research gap through a qualitative study of physician champions that aimed to capture their challenges and strategies during a large-scale HIT implementation.

Understanding U.S. Adults' Zika Virus Risk Perceptions and Mitigation Behaviors to Improve Technology-Supported Risk Communication.

Understanding public risk perceptions, and how these affect behavior, is critical to public health's ability to leverage technology for risk communications. However, little is known about Zika virus risk perceptions. We addressed this gap by analyzing nationally representative (U.

Understanding the Patterns of Health Information Dissemination on Social Media during the Zika Outbreak.

Social media are important platforms for risk communication during public health crises. Effective dissemination of accurate, relevant, and up-to-date health information is important for the public to raise awareness and develop risk management strategies. This study investigates Zika virus-related information circulated on Twitter, identifying the patterns of dissemination of popular tweets and tweets from public health authorities such as the CDC.