Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Feb 9, 2025
Date Accepted: May 19, 2025
Artificial Intelligence in Medical Questionnaires: Innovations, Diagnosis, and Implications
ABSTRACT
To explore the potential of AI-driven methodologies, including machine learning and natural language processing, to improve the design, evaluation, and predictive capabilities of medical questionnaires.Medical questionnaires have traditionally been limited by biases, inefficiency, and data distortion. Recent advancements in artificial intelligence offer new opportunities to enhance these instruments. This review examines the application of AI technologies in the development and use of medical questionnaires within clinical and daily living contexts. This review analyze the current state of AI-enhanced questionnaires, focusing on their ability to provide more accurate diagnostic screening, improve workflow efficiency, and detect conditions such as depression, insomnia, and cataracts. And also consider their adaptability to diverse cultural contexts and their potential to support older adults and individuals with disabilities or limited education. AI-enhanced questionnaires demonstrate significant potential for more precise diagnostic screening and early detection of various conditions. They can also adapt to different cultural contexts and improve accessibility for a broader range of individuals. The integration of AI into medical questionnaires can enhance our understanding of the interplay between environmental factors, patient behaviors, and underlying conditions. This can lead to more equitable, efficient, and personalized healthcare delivery.
Citation
The author of this paper has made a PDF available, but requires the user to login, or create an account.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.