AIMC Topic: Consumer Health Information

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AutoDiscern: rating the quality of online health information with hierarchical encoder attention-based neural networks.

BMC medical informatics and decision making
BACKGROUND: Patients increasingly turn to search engines and online content before, or in place of, talking with a health professional. Low quality health information, which is common on the internet, presents risks to the patient in the form of misi...

Concept based auto-assignment of healthcare questions to domain experts in online Q&A communities.

International journal of medical informatics
BACKGROUND: Healthcare consumers are increasingly turning to the online health Q&A communities to seek answers for their questions because current general search engines are unable to digest complex health-related questions. Q&A communities are platf...

What do patients learn about psychotropic medications on the web? A natural language processing study.

Journal of affective disorders
BACKGROUND: Low rates of medication adherence remain a major challenge across psychiatry. In part, this likely reflects patient concerns about safety and adverse effects, accurate or otherwise. We therefore sought to characterize online information a...

Using Lexical Chains to Identify Text Difficulty: A Corpus Statistics and Classification Study.

IEEE journal of biomedical and health informatics
Our goal is data-driven discovery of features for text simplification. In this paper, we investigate three types of lexical chains: exact, synonymous, and semantic. A lexical chain links semantically related words in a document. We examine their pote...

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

AMIA ... Annual Symposium proceedings. AMIA Symposium
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 strat...

Qcorp: an annotated classification corpus of Chinese health questions.

BMC medical informatics and decision making
BACKGROUND: Health question-answering (QA) systems have become a typical application scenario of Artificial Intelligent (AI). An annotated question corpus is prerequisite for training machines to understand health information needs of users. Thus, we...

Classifying Chinese Questions Related to Health Care Posted by Consumers Via the Internet.

Journal of medical Internet research
BACKGROUND: In question answering (QA) system development, question classification is crucial for identifying information needs and improving the accuracy of returned answers. Although the questions are domain-specific, they are asked by non-professi...

A deep learning approach for predicting the quality of online health expert question-answering services.

Journal of biomedical informatics
Recently, online health expert question-answering (HQA) services (systems) have attracted more and more health consumers to ask health-related questions everywhere at any time due to the convenience and effectiveness. However, the quality of answers ...

Combining Open-domain and Biomedical Knowledge for Topic Recognition in Consumer Health Questions.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Determining the main topics in consumer health questions is a crucial step in their processing as it allows narrowing the search space to a specific semantic context. In this paper we propose a topic recognition approach based on biomedical and open-...