PRIOR KNOWLEDGE CHECK!

What role does AI play in medical diagnostics?

• Improving accuracy and efficiency in medical diagnostics.

• AI is primarily used for patient scheduling.

• AI has no impact on medical diagnostics.

• AI replaces doctors in all diagnostic processes.

How can AI improve the accuracy of disease detection?

• AI improves disease detection accuracy using pattern recognition in data, machine learning and decision support.

• AI can only detect diseases through human intervention.

• AI reduces the need for data analysis in disease detection.

• AI relies solely on historical data without learning from new cases.

What is predictive analytics and how is it used in healthcare?

• It is a method that solely focuses on historical data without future predictions.

• Predictive analytics is only used for financial forecasting in healthcare.

• It helps in forecasting patient risk, treatment optimization, and operational improvements.

• Predictive analytics is a type of medical treatment for patients.

What role does data mining play in enhancing predictive analytics for healthcare?

• Data mining helps in uncovering hidden patterns in patient data to improve predictive models.

• Data mining is irrelevant to healthcare analytics.

• It solely focuses on patient billing information.

• Data mining does not require any historical data.

What are the key challenges in managing patient data with AI?

• Healthcare staffing issues

• Data storage costs

• Data privacy, data quality, integration of data sources, regulatory compliance, and algorithmic bias.

• Patient satisfaction metrics

How does AI enhance patient data management systems?

• AI reduces the need for patient data altogether.

• AI improves efficiency, accuracy, and analytics in patient data management systems.

• AI complicates data entry processes for healthcare providers.

• AI eliminates the need for data security measures in patient management.

What ethical concerns arise from the use of AI in medicine?

• Patient privacy, algorithmic bias, lack of transparency

• Increased patient satisfaction

• Lower healthcare costs

• Enhanced diagnostic accuracy

How can bias in AI algorithms affect patient care?

• Bias in AI algorithms can lead to unequal treatment and disparities in patient care.

• Bias in AI algorithms ensures equal access to care.

• Bias in AI algorithms has no impact on treatment decisions.

• Bias in AI algorithms improves patient outcomes.

How can healthcare professionals ensure ethical AI implementation?

• Ignore data security concerns

• Establish guidelines for data privacy and transparency, involve diverse stakeholders, audit for bias, and train staff on ethics.

• Limit AI use to only administrative tasks

• Rely solely on automated systems without human oversight

Machine learning means learning from

• Machines

• Data

• Books

• Humans