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This Padlet was created to help educate people on the use of AI in healthcare. Because healthcare is so broad, AI is used in a number of ways both clinically and non-clinically. Some clinical examples include radiology, screening, disease diagnosis, and telemedicine. AI is an amazing tool in early diagnosis and treatment of diseases. AI is allowing people to live much longer and survive illnesses they might not have in the past.

Some non-clinical examples include medial administrative tasks, scheduling, finances, and future planning. AI has the ability to automate electronic medical records and make them easily accessible to patients and physicians. AI is excellent at completing routine tasks which allows administrators, physicians, and other healthcare professionals to focus on complex problems.

My interest in the industry is simply the fact that I am applying to nursing school this fall. I have always had an interest in healthcare and completing this research can help myself in my career as well as others. One thing for certain about AI is that it is not going anywhere and it is better to learn about it and be skilled in it than not.

This Padlet wall includes many different posts. The first three give an overview about three major uses of AI in healthcare. They are, medical diagnostics, chronic disease management, and robotic surgery. This wall then covers the future and ethical implications of AI where I discuss where AI has the potential to go and potential issues. I will also cover the societal impact of AI in healthcare. There is also a reflection, a video, citations.

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AI is changing lives when it comes to catching and treating diseases early on. Applying AI to patient results from diagnostic tests allows doctors to diagnose diseases such as pulmonary hypertension and cardiac amyloidosis in the beginning stages. Both of which are fatal if left untreated and are hard to diagnose in early stages. The goal at Johnson and Johnson is to develop AI-enhanced tools to seamlessly aid physicians in diagnostics. AI is being used to scan electrocardiograms for subtleties that are invisible to the naked eye. Even a small lead is enough to flag a patient for further testing and a proper diagnosis. Not everything with AI will be seamless. Some future challenges might include things like the cost of the new technology and training physicians on how to use it.

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Detecting cardiac amyloidosis using AI and the ECG

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AI has the potential to really improve the livelihoods of the chronically ill community. AI can be used in several ways including small things like improving the quality of patient calls and large ways like identifying patients who are at risk of conditions worsening and creating effective condition management. AI can read through patient charts and make connections about their body as a whole that a doctor may not be able to see.

There can be downsides to AI in this setting as well as positives. AI cannot replace the human connection between a care provider and the patient. AI cannot replace emotional support provided by a human and is not intended to replace humans but rather enhance human capabilities. In the future, it is expected that there will be an increase in chronic disease management with AI.

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Robots are now being programmed with AI based surgical systems to aid doctors in streamline surgeries. By using a camera, AI can functionally watch a surgeon in an operating room and make suggestions. AI has already observed millions of surgical videos to the point where it can predict what is going to happen next in an operation within the next 15 to 30 seconds.

AI has the ability to basically be a partner to a surgeon in the operating room and provide safer surgeries to patients. There are challenges like when the doctor and the AI do not agree on something or that a camera is not well positioned. This technology is designed to become more and more mainstream in the future. Currently it is believed to be unlikely, but these technologies have the potential to do the majority of surgeries in the future.

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Future trends and ethical considerations

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Future trends and ethical considerations

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The current trend of AI is that it is absolutely booming. New technologies are being designed and tried everyday. Since the 2000s, AI has been used in chatbots, cars, and some robots. Since ChatGPT and other platforms, AI has become mainstream and used in just about every industry.

AI is going to be used in almost every aspect of healthcare in the future. Some good things will come of it like personalized healthcare for chronically ill people. AI will be more mainstream and will come out with new devices. Some will be worn and be able to constantly monitor people. Early detection of diseases in radiology and pulmonology such as cancers means better chances of survival and increased longevity. With AI's ability to read genetic markers, it will also be able to better treat patients. AI will also include improvements in non-clinical healthcare settings by aiding healthcare administrators. AI will be able to improve electronic medical record storage, medical billing, financing, and staffing.

There are definitely some ethical concerns. There is nothing that can replace a human connection between a patient and a physician or nurse in several aspects but the most important of which being emotional. Another major concern is privacy. Data privacy is a major concern and AI systems need to be carefully monitored to prevent breaches. AI can also create accidental biases which can exacerbate healthcare disparities.

The most important thing is transparency. It is so important to address ethical issues honestly. It is important for health organizations to decide on their own beliefs and how they want to operate. Organizations need to come up with clear guidelines and regulations to govern AI's role in healthcare.

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The societal impact of AI can be a hard concept to fully digest. There are so many things affected by it including employment, privacy and more. AI is able to aid physicians, nurses, and administrators in the field with clinical and non-clinical tasks. AI does a great job completing medial tasks leaving workers more time to do more important things. With the help of AI, workers are able to focus on complex and creative tasks. A problem with AI is potential job displacement involving routine administrative and basic diagnostic processes. AI in the industry forces workers to reskill and upskill for job security purposes. Keeping up with training ensures that professionals can work effectively alongside AI technology.

Privacy is definitely a concern with AI and it is important to ensure robust data protection in order to ensure patient trust and preventing security breaches. It is important to develop strict regulations to ensure proper safety of personal health information.

AI has the opportunity to help develop newer and better processes, perform surgeries with better patient outcomes, and improve efficiency. AI is able to analyze large amounts of information at a rate much faster than a human. Because of chatbots and telemedicine, healthcare is becoming more accessable and is slowly bridging the gaps in quality of care. Unfortunately, because of algorithms, AI unfortunately can cause biases.

These societal impacts give me a greater appreciation for AI. Efficiency in healthcare is so important for staff members as well as patients. As someone looking to pursue a career in healthcare, it is so important to know what you are getting into. Healthcare affects all of us. According to the CDC, more than 51% of all adults have at least one chronic illness and 27% have two or more. AI is going to hopefully be able to help with chronic illness management. My hope is that AI is able to help patients as well as staff in healthcare.

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How artificial intelligence could impact health care

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Here is another brief overview video.

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My research process was that I knew I wanted to do my project about healthcare because that fascinates me the most. Also I am a pre-nursing student currently. I went into ChatGPT to give me inspiration about how AI impacted healthcare and it gave me several directions I could go in for my project. From there I was able to conduct research and figure out my three technologies to write about.

The biggest challenge for me was researching the societal and future impacts of AI. AI can go in so many different directions and it is constantly evolving. We as a society can make predictions but it is hard to say exactly what we are getting ourselves into. AI is the future, that is for sure and it is important to learn about it because it is only expanding.

AI in my chosen industry is very exciting but overwhelming. I am looking forward to seeing how AI is able to improve diagnostic testing and chronic illness management. This research if anything has made me realize that AI is not hypothetical anymore, it is being used everyday. AI is something that I will be trained on as a nurse and will be a part of my daily life.

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1. Johnson & Johnson. (n.d.). Artificial intelligence in healthcare. Retrieved August 3, 2024, from [https://www.jnj.com/innovation/artificial-intelligence-in-healthcare](https://www.jnj.com/innovation/artificial-intelligence-in-healthcare?&utm_source=google&utm_medium=cpc&utm_campaign=GO-USA-ENG-PS-Corporate+Equity-GP-EX-RN-NB_STORIES_ARTIFICIAL+INTELLIGENCE&utm_content=AI+-+Healthcare&utm_term=ai+in+medical+imaging&gad_source=1&gclid=CjwKCAjwqre1BhAqEiwA7g9QhqYk3erPG1SrFyeWMKdRmwKtqhVnAfTp_6Ni52oEq6Dhtz3VwrVnTBoCBtgQAvD_BwE&gclsrc=aw.ds)

2. Veritasium. (2023, May 17). Why it's almost impossible to generate random numbers. YouTube. [https://www.youtube.com/watch?v=zuwjqqAwov0](https://www.youtube.com/watch?v=zuwjqqAwov0)

3. ChartSpan. (2023, January 12). The role of artificial intelligence (AI) in chronic disease management. ChartSpan. Retrieved August 3, 2024, from [https://www.chartspan.com/blog/the-role-of-artificial-intelligence-ai-in-chronic-disease-management/](https://www.chartspan.com/blog/the-role-of-artificial-intelligence-ai-in-chronic-disease-management/)

4. Nature. (2023). Artificial intelligence in healthcare: Transformative potential and ethical considerations. Nature Digital Medicine, 6(2), 112. [https://www.nature.com/articles/s41746-023-00913-9](https://www.nature.com/articles/s41746-023-00913-9)

5. International SOS. (2023, March 25). How AI is transforming the future of healthcare. International SOS Magazine. Retrieved August 3, 2024, from [https://www.internationalsos.com/magazine/how-ai-is-transforming-the-future-of-healthcare](https://www.internationalsos.com/magazine/how-ai-is-transforming-the-future-of-healthcare)

6. Centers for Disease Control and Prevention. (2020). Chronic diseases in America. CDC. Retrieved August 3, 2024, from [https://www.cdc.gov/pcd/issues/2020/20_0130.htm](https://www.cdc.gov/pcd/issues/2020/20_0130.htm#:~:text=More%20than%20half%20(51.8%25),adults%20had%20multiple%20chronic%20conditions)

7. XSOLIS. (2023, April 20). The evolution of AI in healthcare. XSOLIS Blog. Retrieved August 3, 2024, from [https://www.xsolis.com/blog/the-evolution-of-ai-in-healthcare/](https://www.xsolis.com/blog/the-evolution-of-ai-in-healthcare/)

8. TEDx Talks. (2019, June 27). How AI is changing the future of healthcare | Rajiv Khanna | TEDxDallas. YouTube. [https://www.youtube.com/watch?v=NcZpwTCcijE](https://www.youtube.com/watch?v=NcZpwTCcijE)

9.OpenAI. (2024). ChatGPT (GPT-4) [Large language model]. Retrieved from https://www.openai.com/chatgpt