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

摘要

Patients often turn to search engines and online content before, or in place of, talking with a health professional [ ]. However, online health information is not regulated, and prior studies have found wide variations in information quality [ ]. Poor risk communication, biased writing, and lack of transparency about the source of the information plague online health texts [ , ]. This presents a real risk to patients, in the form of misinformation [ – ] and negatively affecting their interactions with health care providers [ , ].