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Setting Expectations for AI Models in Medicine

Artificial intelligence is a hot topic in every field, and these algorithms are being widely used in scientific research. Particularly in my field of genetics and genomics, machine learning methods are invaluable for gleaning insights from large amounts of highly dimensional data. But there are many things to consider before applying AI and ML in a clinical setting, when real people are on the other end of the predictive model. It is important to set expectations for what AI can and cannot accomplish and what is needed for a broad application of AI in medicine in the future. In the session “Hype or Hope? Artificial Intelligence and Machine Learning in Imaging”, presenters gave a great overview of the applications of AI, its limitations, and the advancements that are needed for a wide application of AI in medicine.

Dr. Geoffrey Rubin described many different scenarios in which AI can be deployed. Specifically, he talked about how AI can be used in predictive analytics to make test selection and imaging more efficient, in image reconstruction to reduce noise, in image segmentation to identify regions of interest and provide quantitative analysis, and in interpretation to derive unique characteristics that cannot be measured directly, identify abnormalities, and create reports. In addition, Dr. Tessa Cook explained in greater depth how AI can be used as clinical decision support to incorporate diverse data types and aid in proper test selection. Dr. Damini Dey also discussed how AI can improve diagnosis and prediction, characterize disease, and personalize therapy. Overall, it is important to determine where AI can provide the greatest value while introducing the least amount of risk.

However, there are many limitations to AI and ML models. First, as Dr. David Ouyang noted, because these models are trained by humans, they can only perform tasks that a human could theoretically do. AI just performs these tasks faster, more consistently, and at a larger scale. He noted that these models are not effective unless trained on broad underlying datasets, and that unless explicitly programmed, they do not accurately weight rare significant events. AI models can easily become uninterpretable black boxes, keeping experts from recognizing where they are failing. Dr. David Playford emphasized that due to these and other limitations, AI models are not yet clinically accurate in all areas.

There are many steps that must be taken before AI models can achieve wide use in clinical settings. Dr. Ouyang suggests standardized baselines and open access to measure advancements among tools. Dr. Cook implements a “trust and value” checklist to assess how each tool was trained and tested, as well as what it can and cannot do, before using it for clinical decision support. Dr. Playford advocates for randomized trials to establish proof-of-concept and compare outcomes to the current standard of care. Most importantly, steps must be taken to reduce bias in AI models, which can negatively impact the care of underrepresented populations. Multidisciplinary collaborative teams can ensure that the data aligns with the clinical question being tackled, diverse yet consistent training datasets are being used, and methods such as transfer learning are implemented to produce more accurate predictions on previously unseen datasets. While AI can be an important tool in clinical decision making, it is ultimately the responsibility of each physician to ensure that AI tools are serving their patients as effectively as possible.

“The views, opinions and positions expressed within this blog are those of the author(s) alone and do not represent those of the American Heart Association. The accuracy, completeness and validity of any statements made within this article are not guaranteed. We accept no liability for any errors, omissions or representations. The copyright of this content belongs to the author and any liability with regards to infringement of intellectual property rights remains with them. The Early Career Voice blog is not intended to provide medical advice or treatment. Only your healthcare provider can provide that. The American Heart Association recommends that you consult your healthcare provider regarding your personal health matters. If you think you are having a heart attack, stroke or another emergency, please call 911 immediately.”

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Overcoming Imposter Syndrome

This year’s AHA Scientific Sessions has a strong focus on racial and gender diversity and equity, as well as creating inclusive environments in science and medicine. It is great to see that there are increasingly more opportunities opened up to people who are traditionally underrepresented, but there are still challenges that are faced when we get there. One discussion that really interested me focused on one of those challenges: imposter syndrome.

Imposter syndrome is an internal struggle. It is the inability to recognize your own success; the feeling that you don’t belong somewhere and will soon be outed as a fraud. As a Black woman and the youngest person in my PhD cohort, it is a feeling that I have felt too many times to count. Imposter syndrome can cause you to self-sabotage by not applying to opportunities, missing deadlines, or avoiding networking because you feel that you do not belong in that space. The panelists today – Dr. Toniya Singh, Dr. Gina Lundberg, Dr. Aaysha Cader, Dr. Ambreen Mohamed, Dr. Aamisha Gupta, Dr. Janet Han, and Dr. Nasrien Ibrahim – discussed the ways in which we can overcome imposter syndrome and reach our fullest potential.

When feelings of inadequacy first appear, it is important to recognize that feelings are not fact. Dr. Gupta stresses defining the facts by listing your accomplishments and qualifications. Reframe your thoughts to center everything you contribute instead of the credit you think you should get. Women, in particular, tend to underestimate themselves, so it is helpful to have a diverse circle of friends and allies that can be honest with you, encourage you, and advocate for you to others. If you have the means, having a career coach can help you to focus on your goals while providing honest and objective feedback on strengths and weaknesses. It is an invaluable investment in yourself. Imposter syndrome can also make public speaking difficult. Dr. Lundberg suggests focusing on presenting for one specific person instead of a large audience. Remind yourself that you are the expert here and that everyone who is watching wants you to be yourself and to succeed.

Regular self-reflection can help quickly overcome imposter syndrome in the future. Dr. Cader emphasizes aligning your behaviors with your values so there is no dissonance between what you are doing and what you want. Finding intrinsic value in the things that you do can make it easier to recognize your achievements. When you put time into doing what you love, you can’t help but dream big. This panel reminded me that imposter syndrome is something many people go through and that you can experience it and still be successful. Talking about your experiences can help everyone overcome this challenge so that when opportunities arise, we don’t hesitate to take them.

 

“The views, opinions and positions expressed within this blog are those of the author(s) alone and do not represent those of the American Heart Association. The accuracy, completeness and validity of any statements made within this article are not guaranteed. We accept no liability for any errors, omissions or representations. The copyright of this content belongs to the author and any liability with regards to infringement of intellectual property rights remains with them. The Early Career Voice blog is not intended to provide medical advice or treatment. Only your healthcare provider can provide that. The American Heart Association recommends that you consult your healthcare provider regarding your personal health matters. If you think you are having a heart attack, stroke or another emergency, please call 911 immediately.”