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1


What is the primary goal of the article according to its introduction?

3. To explore advancements, applications, and challenges of generative AI in medical imaging

“Seminal works published since 2022 in medical imaging have shown the potential of generative artificial intelligence in creating realistic medical images (synthetic data), suggesting new approaches for research and clinical applications.” it shows overview of synthetic data and analyses the advancements, applications, and challenges

The introduction focuses on generative AI in medical imaging

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2


How do generative AI models differ from traditional discriminative models in healthcare applications?

2. Generative models produce new data rather than only classify or interpret

“Generative artificial intelligence is a class of deep learning models capable of creating content that diverges from traditional discriminative models focused on interpretation or decision making.” It says it is capable of creating content.

From the sentence mentioned above, it contrasts generative artificial intelligence with traditional discriminative models.

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3


What is meant by the term “model as a dataset”?

3. Sharing trained model weights instead of raw data

“The advancement of generative artificial intelligence introduces a new concept in data sharing, which we refer to as a model as a dataset.” "“Unlike traditional dataset sharing, which involves transferring actual images, sharing model weights provides an efficient alternative that allows others to generate new synthetic images with properties similar to the original data.”

It says "model as a dataset", sharing model weights allows new synthetic images.

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4


Which statement correctly distinguishes physics-informed and statistical models?

3. Physics-informed models incorporate biological or physical principles

“Rather than learning the patterns directly from data, these models encode expert knowledge and known physics laws (eg, fluid dynamics, tissue biomechanics, or radiation physics) to simulate biological phenomena.”

So it means that, physics-informed model incorporate biological principles too.

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5


According to the article, what does the “image generation trilemma” describe?

2. Trade-offs among image diversity, quality, and speed

“Statistical models encounter the generative artificial intelligence trilemma, which involves balancing high sample quality, comprehensive mode coverage, and rapid sampling rates (figure 2).” AI models must balance these 3 factors.

the text describes the image generation trilemma as the trade-off among diversity, quality, and speed in image generation.

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6


What is the Human Turing Test used for in medical image synthesis?

2. To assess realism of synthetic medical images by experts

“The human Turing test involves domain experts who are asked to discern between real and derived medical images. This assessment provides insights into the perceptual quality and realism of generated images, which is crucial for medical imaging, in which accuracy and fidelity are paramount.” This shows that it provides insight into quality and realism.

Domain experts are asked to compare between real and generated images, to see whether the generated images are real enough or not.

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7


Which of the following is NOT mentioned as a potential benefit of synthetic data in healthcare?

4. Eliminating all medical biases permanently

"their ability to increase dataset size and diversity," "offer a privacy-preserving solution…", "…enabling privacy-preserving multicentre collaborations…," …enhancing medical education…" The benefits are talked about.

The text does not mention Eliminating all medical biases Permanently. Only some benefits.

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8


What is one major ethical concern associated with generative AI in medical imaging?

2. Data copying and patient reidentification

“inadvertently reveal sensitive patient information when they reproduce images that closely resemble the original data.” There is a risk of data copying and patient privacy.

It is found in "Patient privacy and data copying" in the Challenges and consideration.

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9


What regulatory precedent did the article cite for synthetic data technologies?

2. FDA clearance of synthetic MRI as image-processing software

“Frameworks for evaluating synthetic medical imaging are already emerging, as evidenced by the FDA’s clearance of synthetic MRI technologies. These technologies were regulated as image-processing software rather than as completely novel modalities.” There is evidence of FDA's clearance, and the technologies were regulated as an image-processing software.

It is in the future direction section, FDA clearance of synthetic MRI technologies which will be regulated as image-processing software.

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10


What is the main purpose of the article?

2. To compare and evaluate ASCVD risk prediction models in East Asia

“This study aims to evaluate and compare cardiovascular risk prediction models developed in Western countries and those specific to East Asian populations.” It says it aims to evaluate and compare

It is found in the ASCVD introduction. It mentions east asia countries and comparing between them.

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11


Which of the following models was originally developed for a Western population?

1. Framingham Risk Score

“The Framingham Risk Score, developed in the United States using data from the Framingham Heart Study, represents one of the most widely used risk models in Western populations.”

found in the background paragraph describing model origin

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12


Why might Western-based risk prediction models overestimate ASCVD risk in East Asian populations?

2. East Asians have lower baseline incidence of ASCVD

“In this overview of ASCVD risk assessment in East Asian countries, specifically China, Japan, and South Korea, ASCVD risk is significantly overestimated, in particular CHD, when applying calculators developed in the United States including the FRS and PCE. Unlike Europe and the United States, incidence of CHD is much lower while stroke rates are higher in Japan, Korea, and China.”

east asians have lower CHD incidence, applying Western models overestimates their ASCVD risk

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13


What is the key advantage of the China-PAR model compared to Western-based models?

4. It was calibrated using national data representing diverse regions in China

“The China-PAR (Prediction for ASCVD Risk in China) project found that the PCE had low discrimination ability and poor calibration for Chinese men. These findings highlighted the importance of developing CVD risk prediction models based on data from Chinese cohort studies.”

China PAR model was specifically calibrated with nationwide Chinese data

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14


Which of the following variables is not typically included in ASCVD risk prediction models discussed in the article?

4. Genetic ancestry markers

“These models typically include factors such as age, blood pressure, serum cholesterol, and smoking status...” It does not mention genetic ancestry makers.

Genetic ancestry makers are not mentioned, so it is not a common practice.

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15


What is a major difference between the Suita Score and the Framingham Risk Score?

2. Suita Score was designed for a Japanese population using local epidemiological data

“In the 2017 JAS guideline, the Suita score was able to accurately estimate the absolute incidence of CHD by incorporating demographics and risk factors including age, sex, smoking, blood pressure level, HDL-C, LDL-C, impaired glucose tolerance, and family history of premature CHD. The Suita score was chosen from 10 different published risk prediction scores in Japan where internal validation was carefully performed.” “The Suita Score was developed using Japanese cohort data from the Suita Study, while the Framingham Risk Score was based on Western (U.S.) populations.”

suita was developed and validated using Japanese population data

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16


According to the article, what is a potential benefit of developing East Asia–specific risk models?

3. They improve accuracy and reduce overestimation of risk

“In this overview of ASCVD risk assessment in East Asian countries, specifically China, Japan, and South Korea, ASCVD risk is significantly overestimated, in particular CHD, when applying calculators developed in the United States including the FRS and PCE. Unlike Europe and the United States, incidence of CHD is much lower while stroke rates are higher in Japan, Korea, and China. Studies to recalibrate these risk scores have been unsatisfactory, resulting in each country developing their own risk prediction scores based on epidemiologic studies using native cohorts and traditional risk factors.”

developing east asia specific models helps increase accuracy by using local data

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17


Which factor was highlighted as influencing ASCVD risk differences among East Asian countries?

2. Cultural and dietary variations, such as salt intake and lifestyle

“Differences in ASCVD risk across East Asian countries have been attributed to variations in dietary patterns, salt consumption, physical activity, and lifestyle behaviors, as well as differences in healthcare systems and prevention strategies.” It states that these factors may affect the differences between each persons' risk.

environmental and behavioral factors significantly affect the progression of cardiovascular diseases in different populations

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18


What future direction does the article suggest for improving ASCVD risk prediction?

2. Using multimodal AI-based prediction integrated with regional data

“Future research should focus on developing AI-driven, multimodal prediction models that integrate clinical, imaging, genetic, and regional population data to enhance ASCVD risk prediction accuracy and applicability across diverse East Asian populations.”

AI integration and multimodal data fusion in producing region-specific cardiovascular risk assessments

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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?

3. DDPMs iteratively remove noise through reverse diffusion rather than using encoder–decoder or discriminator structures.

“Denoising diffusion probabilistic models (DDPMs) introduce noise into an image and learn to reverse this process, producing high-quality samples.”

image generation is treated as a denoising process, distinguishing DDPMs to models like VAEs and GANs.

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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?

3. Despite differences in age structures, Japan maintains low mortality rates in both measures, suggesting effective prevention and healthcare systems.

“Of the 5 major countries of this region, South Korea had the lowest crude CVD mortality rate (145 of 100,000) while North Korea had the highest (391 of 100,000). … Japan had the lowest proportion of stroke deaths (39%), while China (48%) and South Korea (47%) had comparable rates.”

This indicates that Japan despite being an aging society, consistently shows low CVD mortality rates which means they have strong prevention, healthcare, and population health management.

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ผลคะแนน 132.65 เต็ม 140

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