| 1 |
What is the primary goal of the article according to its introduction?
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To evaluate economic impacts of AI technology |
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| 2 |
How do generative AI models differ from traditional discriminative models in healthcare applications?
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Generative models produce new data rather than only classify or interpret |
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| 3 |
What is meant by the term “model as a dataset”?
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Sharing trained model weights instead of raw data |
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| 4 |
Which statement correctly distinguishes physics-informed and statistical models?
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Statistical models are limited to MRI reconstruction |
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| 5 |
According to the article, what does the “image generation trilemma” describe?
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Ethical issues in synthetic image use |
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| 6 |
What is the Human Turing Test used for in medical image synthesis?
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To calculate mathematical similarity scores |
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| 7 |
Which of the following is NOT mentioned as a potential benefit of synthetic data in healthcare?
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Facilitating multi-centre collaborations |
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| 8 |
What is one major ethical concern associated with generative AI in medical imaging?
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Lack of sufficient datasets |
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| 9 |
What regulatory precedent did the article cite for synthetic data technologies?
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WHO approval of AI diagnostic models |
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| 10 |
What is the main purpose of the article?
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To compare and evaluate ASCVD risk prediction models in East Asia |
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| 11 |
Which of the following models was originally developed for a Western population?
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Korean Risk Prediction Model (KRPM) |
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| 12 |
Why might Western-based risk prediction models overestimate ASCVD risk in East Asian populations?
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Data collection standards are weaker in Asia |
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| 13 |
What is the key advantage of the China-PAR model compared to Western-based models?
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It uses imaging biomarkers only |
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| 14 |
Which of the following variables is not typically included in ASCVD risk prediction models discussed in the article?
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Blood pressure |
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| 15 |
What is a major difference between the Suita Score and the Framingham Risk Score?
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Suita Score predicts lifetime risk instead of 10-year risk |
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| 16 |
According to the article, what is a potential benefit of developing East Asia–specific risk models?
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They reduce the need for clinical validation |
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| 17 |
Which factor was highlighted as influencing ASCVD risk differences among East Asian countries?
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Cultural and dietary variations, such as salt intake and lifestyle |
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| 18 |
What future direction does the article suggest for improving ASCVD risk prediction?
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Using multimodal AI-based prediction integrated with regional data |
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| 19 |
Which statement best explains the key difference in how VAEs, GANs, and DDPMs generate medical images according to the figure?
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DDPMs iteratively remove noise through reverse diffusion rather than using encoder–decoder or discriminator structures. |
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| 20 |
Which of the following best explains the trend shown in Figure comparing age-standardized and crude CVD mortality rates among East Asian countries?
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Mongolia and North Korea demonstrate higher CVD mortality due to older population structures alone. |
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