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Discuss, Learn and be Happy דיון בשאלות

In medical data science, causal inference is primarily used to:

When a predictive model in medicine shows extreme class imbalance, what is the best way to evaluate performance?

A hospital is using an AI system to predict heart attack risk. The model has high sensitivity but low specificity. What does this mean?

In medical AI models, fairness issues often arise when:

Which performance metric is most important for identifying rare diseases?

A doctor is concerned that a predictive model for sepsis has low Positive Predictive Value (PPV). What does this mean in practice?

Which of the following is an example of bias in the dataset?

In 2018, Amazon discontinued an AI-based recruiting tool due to fairness concerns. What was the main issue?

Which of the following best describes "multi-calibration" in predictive models?

Which method is NOT used for model explainability?

ביו-אינפורמטיקה רפואית

Discuss, Learn and be Happy דיון בשאלות

In medical data science, causal inference is primarily used to:

When a predictive model in medicine shows extreme class imbalance, what is the best way to evaluate performance?

A hospital is using an AI system to predict heart attack risk. The model has high sensitivity but low specificity. What does this mean?

In medical AI models, fairness issues often arise when:

Which performance metric is most important for identifying rare diseases?

A doctor is concerned that a predictive model for sepsis has low Positive Predictive Value (PPV). What does this mean in practice?

Which of the following is an example of bias in the dataset?

In 2018, Amazon discontinued an AI-based recruiting tool due to fairness concerns. What was the main issue?

Which of the following best describes "multi-calibration" in predictive models?

Which method is NOT used for model explainability?