Considerations for Developing Diagnostic Artificial Intelligence: Towards Real-World Application of an Asthma Detection Model

Author:

Kim Taeyoung1ORCID,Chung Myung Jin12ORCID

Affiliation:

1. Medical AI Research Center, Samsung Medical Center, Seoul, Korea.

2. Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.

Publisher

XMLink

Reference9 articles.

1. U.S. Food and Drug Administration. Artificial Intelligence and Machine Learning (AI/ML)-Enabled Medical Devices [Internet]. Silver Spring (MD). U.S. Food and Drug Administration. 2023. cited 2023 Dec 12. Available from: https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-aiml-enabled-medical-devices

2. Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs

3. An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction

4. Artificial intelligence in radiology: 100 commercially available products and their scientific evidence

5. Artificial intelligence as a medical device in radiology: ethical and regulatory issues in Europe and the United States

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