Accuracy and comprehensibility of chat-based artificial intelligence for patient information on atrial fibrillation and cardiac implantable electronic devices.
Henrike Aenne Katrin HillmannEleonora AngeliniNizar KarfoulSebastian FeickertJohanna Mueller-LeisseDavid DunckerPublished in: Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology (2023)
Responses generated by an NLPC are mostly easy to understand with varying readability between the different NLPCs. Appropriateness of responses is limited and varies between different NLPC. Important aspects are often missed to be mentioned. Thus, chatbots should be used with caution to gather medical information about cardiac arrhythmias and devices.
Keyphrases
- artificial intelligence
- health information
- atrial fibrillation
- machine learning
- big data
- deep learning
- left ventricular
- healthcare
- heart failure
- case report
- social media
- left atrial appendage
- congenital heart disease
- direct oral anticoagulants
- acute coronary syndrome
- percutaneous coronary intervention
- coronary artery disease
- venous thromboembolism
- mitral valve