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How AI can heal healthcare | Edmund Jackson | TEDxNashville

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Future Trends and Ethical Considerations

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Future Trends and Ethical Considerations

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Artificial Intelligence in healthcare is changing rapidly with future trends looking towards even more personalized, preventative, and predictive care. One developing healthcare artificial intelligence tool is the creation of digital twins. The virtual model of patients that simulate treat responses before actual application. As well as, shows advances in predictive genomics that will allow artificial intelligence to predict and detect diseases before symptoms even appear. creating more positive, productive and proactive outcomes. Artificial intelligence will also integrate and combine more deeply with wearable technologies, creating a smooth and reliable real time health management ecosystems that reduce and limit hospital visits and prioritize preventable health care.

These innovations although positive raise great concerns about the storage of sensitive medical information. If the data is misused it can introduce privacy risks. Especially if the data is mishandled by corrupt corporate companies or insurers. Artificial intelligence systems can also accidentally inherit a bias from their training. This can lead to unequal care for disadvantage communities.This can be concerning.

I personally see a great potential for Artificial intelligence growth to bring help to other underserved regions. I am also greatly concerned about over reliance on artificial intelligence algorithms in decision making. It can be difficult to balance innovation with a strict ethical framework but this is very important in the healthcare industry to make sure everyone receives fair treatment, and optimal care.

References

Davenport, T., & Kalakota, R. (2019). The potential for artificial intelligence in healthcare. Future Healthcare Journal, 6(2), 94–98. https://doi.org/10.7861/futurehosp.6-2-94

Topol, E. (2019). Deep medicine: How artificial intelligence can make healthcare human again. Basic Books.

Yu, K.-H., Beam, A. L., & Kohane, I. S. (2018). Artificial intelligence in healthcare. Nature Biomedical Engineering, 2(10), 719–731. https://doi.org/10.1038/s41551-018-0305-z

Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., Wang, Y., Dong, Q., Shen, H., & Wang, Y. (2017). Artificial intelligence in healthcare: Past, present and future. Stroke and Vascular Neurology, 2(4), 230–243. https://doi.org/10.1136/svn-2017-000101

Reddy, S., Fox, J., & Purohit, M. P. (2019). Artificial intelligence-enabled healthcare delivery. Journal of the Royal Society of Medicine, 112(1), 22–28. https://doi.org/10.1177/0141076818815510

Esteva, A., Robicquet, A., Ramsundar, B., Kuleshov, V., DePristo, M., Chou, K., Cui, C., Corrado, G. S., Thrun, S., & Dean, J. (2019). A guide to deep learning in healthcare. Nature Medicine, 25(1), 24–29. https://doi.org/10.1038/s41591-018-0316-z

Beam, A. L., & Kohane, I. S. (2018). Big data and machine learning in health care. JAMA, 319(13), 1317–1318. https://doi.org/10.1001/jama.2017.18391

Obermeyer, Z., & Emanuel, E. J. (2016). Predicting the future — Big data, machine learning, and clinical medicine. The New England Journal of Medicine, 375(13), 1216–1219. https://doi.org/10.1056/NEJMp1606181

Davenport, T., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108–116. https://hbr.org/2018/01/artificial-intelligence-for-the-real-world

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Equity is a concerning issue in regards to artificial intelligence in our society. Healthcare systems that the economic resources may use AI more frequently in comparison to environments that don’t. Potentially creating a greater gap. Without careful policies to reinforce an equitable environment. AI could accidentally reinforce Systematic issues rather than solve them.

Another concern is job displacement because of the transformation of AI in our society. This leaves careers with different roles. It can be concerning for professions like radiologists, transcriptionists, scribes, and other roles impacted by automation. It also leaves a good opportunity for new Opportunities to develop in AI development. This requires the reshaping and reskilling of the workforce. Privacy risk remain critical. As AI data sets are constantly. Depending on extensive medical information, not known to the average public.

As a future healthcare professional, I am excited to use artificial intelligence in the workplace. I believe ethical deployment is important though to ensure that no group is marginalized. It is important to balance, AI and human professional input to ensure the best care is given possible.

Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., Wang, Y., Dong, Q., Shen, H., & Wang, Y. (2017). Artificial intelligence in healthcare: Past, present and future. Stroke and Vascular Neurology, 2(4), 230–243. https://doi.org/10.1136/svn-2017-000101

Mak, K. K., & Pichika, M. R. (2018). Artificial intelligence in drug development: Present status and future prospects. Current Opinion in Pharmacology, 42, 81–89. https://doi.org/10.1016/j.coph.2018.06.004

National Cancer Institute. (n.d.). Definition of personalized medicine. U.S. Department of Health and Human Services. https://www.cancer.gov/publications/dictionaries/cancer-terms/def/personalized-medicine

Topol, E. (2019). Deep medicine: How artificial intelligence can make healthcare human again. Basic Books.

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It is very interesting to see and potentially us Artifical intelligence as a future healthcare professional, who hopes to use artificial intelligence in the workplace to optimize patient care. It is impressive reflect how precise and analytic artificial intelligence really is. Artificial intelligence can predict cardiovascular disease diseases before symptoms can even appear. It does this by analyzing genetics predicting diseases and customizing care for patients. In the same sense though it also makes me think critically about how important it is to ethically what does that look like in the medical field when using artificial intelligence? I personally feel very optimistic, but I am concerned about data privacy uses and artificial intelligence bias. Artificial intelligence has incredible potential to improve health care all around the world if used ethically correctly

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Personalized medicine is changing healthcare by steering away from traditional treatments towards specific care tailored to an individual’s needs and unique lifestyle, biology, and health history. Rather than prescribing the same type of drug or therapy to every single patient with a particular condition. Personalized medicine uses data like genetics, biomakers, and normal habits to determine what will work best for each person. This method can improve treatment effectiveness, prevent diseases before they even develop, and reduce side effects.

Artificial Intelligence makes this possible. Modern healthcare has a massive amount of information like lab test, data sequences, imaging scans and wearable data. It would be impossible for humans only to analyze alone. For example, Artificial Intelligence can determine which cancer therapy is more likely to benefit a patient based on their genetic profile or it can predict an individual’s risk for developing heart disease or other certain conditions.Using biometrics and information.

Other than treatment selection, AI drives drug discovery by showcasing how certain compounds can interact with genetic variations. Significantly reducing time and costs in comparison to other models. Artificial intelligence enables continuous real time patient monitoring and management. This allows treatments to be dynamically adjusted as health data alters.

By using predictive programming analytics with individualized data. Artificial intelligence driven personalized medicine defines that promise as a future healthcare professional to always give the best optimal care. Making medicine more efficient and patient centered. I think it’s amazing for the future of medicine and healthcare.

Jiang, Fei, et al. “Artificial Intelligence in Healthcare: Past, Present and Future.” Stroke and Vascular Neurology, vol. 2, no. 4, 2017, pp. 230–243.

Mak, K. K., and M. R. Pichika. “Artificial Intelligence in Drug Development.” Current Opinion in Pharmacology, vol. 42, 2018, pp. 81–89.

National Cancer Institute. “Definition of Personalized Medicine.” cancer.gov, U.S. Department of Health and Human Services.

Topol, Eric. Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. Basic Books, 2019.