Early Diagnosis of Hereditary Angioedema in Japan Based on a US Medical Dataset: Algorithm Development and Validation.

Kouhei Yamashita Yuji Nomoto Tomoya Hirose Akira Yutani Akira Okada Nayu Watanabe Ken Suzuki Munenori Senzaki Tomohiro Kuroda

Published in: JMIR medical informatics (2024)

This study indicates that our AI model can detect HAE in patients with typical symptoms and is effective in Japanese data. However, further prospective clinical studies are required to investigate whether this model can be used to diagnose HAE.

Keyphrases

healthcare
machine learning
artificial intelligence
electronic health record
big data
depressive symptoms