These 23 questions were asked during the Q&A section of the AI for Healthcare webinar delivered in November 2020. 
Select the questions you would most like to see answered during the next AI webinar.
You may select up to eight questions. 

Question Title

* 1. As a doctor working from an AI company in San Francisco, how do we collaborate with Australia?

Question Title

* 2. Real-world data is often at risk of bias and missing data. Do you have any recommendations on how data scientists should best collaborate with physicians and clinical scientists?

Question Title

* 3. Any recommendation on how my department could me more involved with AI in Nuclear Medicine?

Question Title

* 4. What skills are needed to be involved in AI research?

Question Title

* 5. How can data linkage across different elements of health care (hospital, primary care, medication dispensing, death data) be used here?

Question Title

* 6. Even if we have clean data and reliable algorithms, we have implementation deficit disorder. How do we get these AI models into clinical practice?

Question Title

* 7. Health care places such an emphasis on clinical coding. Is there any progress in AI enabling this process?

Question Title

* 8. Risks and benefits of using AI in primary and tertiary health care. Capacity building of health professionals in using AI.

Question Title

* 9. Are there some examples of non-image based AI applications being used in clinical medicine?

Question Title

* 10. Can AI be used to improve quality of care? e.g. antimicrobial stewardship, given a lot of hospitals use electronic prescribing and there may be inappropriate selections or durations of antimicrobial treatments

Question Title

* 11. What technique, in your opinion, would you recommend for text classification in health informatics, would you recommend gpt-2?

Question Title

* 12. Can AI be used to improve the running of small private practices?

Question Title

* 13. Interested in AI predictive disease models - Could you give some insights on current development?

Question Title

* 14. What are the AI applications in endocrinology?

Question Title

* 15. Where do you see AI in healthcare in 10 years in Australia?

Question Title

* 16. What about patients that don’t know how to tell us what their symptoms are?

Question Title

* 17. Bias. We hear a lot around AI bias and methods to mitigate this e.g. counterfactual fairness. This concern is brought up a lot regarding racial bias in AI algorithms, including medical algorithms. Are the current methods for mitigating bias, technically easy and robust?

Question Title

* 18. Can AI be created to review our clinical decision-making with the aim of reduce cognitive bias?

Question Title

* 19. You talked about big data. What do you think, the role of 'small data' in medical AI?

Question Title

* 20. How long will it take for your network to learn with a given data sets?

Question Title

* 21. How to use AI clinically to reduce errors in diagnosis, using a usual PC?

Question Title

* 22. How do we guarantee privacy of data?

Question Title

* 23. Won't AI threaten privacy and patient's rights?

T