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The healthcare industry has always been one of the most important industries and a foundation of human well-being, and with the introduction of artificial intelligence (AI), its potential is growing rapidly. The healthcare industry includes all the medical services and businesses that help people stay healthy, such as hospitals, doctors, medicines, and health insurance. I’ve always been interested in healthcare because of its direct impact on people's lives, and I find it amazing how technology can improve medical care. I’ve seen firsthand how medical advances have impacted families, and I understand how important it is to have accessible, effective, and compassionate care. The idea that AI could solve some of healthcare’s biggest problems is exciting. AI in healthcare offers significant improvements in areas like personalized treatment, drug development, and patient care. AI technologies like IBM Watson for Oncology, Exscientia, and Ada Health are making it easier for doctors to make quick and accurate decisions, speed up drug creation, and give patients quick, personalized health advice. However, these changes also come with challenges and ethical concerns, such as doctors relying too much on AI, concerns about protecting patient data, and the possibility of healthcare jobs being lost due to automation. These are important issues to consider as we use AI in healthcare. It’s important to make sure that while AI can make healthcare better, it also benefits everyone fairly and keeps the human side of care intact. AI should help doctors and patients, not replace the essential emotional connection in healthcare. By using AI responsibly, we can make healthcare more efficient, accessible, and better for everyone. This Padlet wall will explore how AI is reshaping the healthcare industry, including the benefits and challenges it brings, and the broader impacts it has on society. It also discusses why it's important to use AI carefully, making sure it supports human healthcare workers instead of replacing them. AI’s potential in healthcare is immense because it can transform lives in ways we couldn’t have imagined before.

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IBM Watson for Oncology uses Clinical Decision Support Systems (CDSS) with AI to help oncologists make better treatment choices for cancer patients. It uses technologies like machine learning, natural language processing (NLP), and data analysis to review large amounts of medical research, clinical trial data, and patient records. This helps IBM Watson recommend the best treatments based on each patient’s unique genetic and medical profile. The main benefits of AI usage include faster, more accurate decisions and treatments that are specific to each patient. However, there are some challenges, such as issues with the quality and organization of data, keeping the system updated with the latest medical research, and the risk that doctors might rely too much on AI instead of using their own knowledge in complicated cases. I find Watson for Oncology interesting because it helps doctors make faster, more personalized treatment decisions for cancer patients. The idea that AI can use a patient's unique data to choose the best treatment is impressive. Though, I do have concerns that doctors might rely on it too much and not trust their own judgment in some cases. I also wonder how hard it must be to keep the system up to date with all the new medical research happening every day.

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Exscientia is a company using AI to speed up the process of discovering new drugs and make it more efficient. Their AI platform uses machine learning, deep learning, and neural networks to study large amounts of data about chemicals and biology. This allows Exscientia to predict how different molecules will work, find potential drug candidates, and improve drug designs. By using AI, the company can shorten the time it takes to make new drugs. Their platform has already helped develop drugs for diseases like cancer and immune disorders, which are now in various stages of clinical trials. The main benefits of AI include quicker drug discovery, better predictions of a drug’s safety and effectiveness, and testing more possible drugs. However, there are challenges, like needing good-quality data, making sure AI models are correct, and fitting AI into the traditional drug development process. I found Exscientia's AI in drug discovery to be fascinating because of the fact that it can speed up the process of finding new treatments for diseases like cancer, which is truly incredible. But I also think it’s crucial to remember that AI should work with experts, not replace them entirely.

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Ada Health is an app that uses an AI-powered virtual health assistant to help users figure out their symptoms and get personalized health advice. Ada lets users share their symptoms through a simple chat using technology like machine learning, natural language processing (NLP), and data analytics. The AI then looks at this information and gives you possible health issues you may have and advice on what to do next. The main benefits of Ada’s virtual assistant are faster access to medical advice, the decreasing of unnecessary doctor visits, and helping users decide if they need further medical attention. However, challenges include making sure the AI gives accurate advice since it can't replace a professional medical diagnosis, as well as ensuring patient data is kept secure (there are privacy and data security concerns). Ada’s AI virtual assistant is also limited by the data it's trained on, which can affect its ability to handle more complicated or rare/unique cases. I think it is a great tool for checking symptoms and getting quick advice and I think it is amazing how it makes healthcare more accessible without needing to visit a doctor right away. However, as I mentioned in my other examples, it’s important to remember that the AI virtual assistant can’t replace a real doctor’s advice.

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Future Trends and Ethical Considerations

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Future Trends and Ethical Considerations

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The future of AI in healthcare looks very promising, with the potential for more personalized treatments, faster drug development, and better patient care. AI systems, like IBM Watson for Oncology and Exscientia, are already helping doctors choose the best treatments and speed up the creation of life-saving drugs. As AI continues to improve, we could see more and more accurate diagnoses and quicker treatments, which could completely revolutionize healthcare. However, there are important ethical issues to consider. For example, if AI makes a mistake or provides wrong recommendations, who should be held accountable? Should it be the AI system, the developers, or healthcare professionals? Another ethical issue to consider is that AI systems need to be continuously updated with the latest medical information because healthcare is always evolving. If the AI technology isn't updated, it could make incorrect decisions based on outdated data, potentially harming patients. Additionally, there's a risk that doctors might become overly reliant on AI, diminishing their trust in their judgment. AI could also reduce human interaction in healthcare, making the experience feel less personal. In my opinion, healthcare is not just about diagnosing and treating diseases, it is also about connecting with patients on an emotional level and having empathy for them. When a doctor shows empathy, listens to concerns, and provides reassurance, it helps patients feel understood and cared for, and it creates a personal connection that builds trust, which is crucial for effective communication and treatment. Personally, I believe AI has the potential to greatly improve healthcare, but it must be used responsibly. We need to determine accountability when AI makes a mistake, keep AI updated with the latest medical information, and preserve the essential human connection in healthcare. AI should work with doctors, not replace them, ensuring that patients get the best care possible and that AI is used to benefit all patients fairly.

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AI in healthcare has a lot of potential, but it also brings important societal impacts that must be considered. One big concern is employment, since it is possible for some jobs for healthcare workers to be replaced by AI automation, especially those that involve repetitive tasks. I personally do not think it is fair or logical that healthcare workers could lose work opportunities to AI. The idea that AI can help healthcare workers by easing their workload is amazing for the healthcare industry, however my perception of AI in this industry has definitely changed for the worse knowing it could cause job loss in certain areas of healthcare. Additionally, since AI systems use large amounts of sensitive health information to work properly, it raises concerns about how this information is protected. If data is hacked or misused, it could have serious consequences, therefore securing patient data is vital. AI affects equity because the AI systems used in healthcare could be biased if the data it’s trained on isn’t diverse enough, leading to unfair treatment or wrong diagnoses for certain groups of people. For example, algorithms that are based on data from just one group could result in incorrect or biased recommendations for others. A positive societal impact of AI in healthcare is that it could make healthcare easier to access since AI tools can help provide quality care to underprivileged communities. While I see the great potential of AI in improving healthcare, these societal impacts make me cautious and highlight the importance of using it carefully. I believe that AI can improve healthcare, but we need to think about how it affects jobs, protects patient privacy, and make sure everyone has equal access to these new advancements. By developing AI responsibly, we can make healthcare better for everyone without making existing problems worse.

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Through my research, I gained a deeper understanding of AI's impact on the healthcare industry, particularly in areas like personalized treatment, drug development, and decision-making. However, AI's impact also raises important ethical concerns, such as job displacement, data privacy, accountability, the risk of biased data in AI systems, and the potential for over-reliance on technology. One challenge I encountered while researching was balancing information from various sources without making it too complicated for the reader. To solve this, I focused on explaining complex ideas clearly and simply while still keeping them accurate. I also found it challenging to find diverse articles (that are credible sources) on AI in healthcare, but by making my search more specific, I was able to overcome this challenge. This research has shown me that AI has the potential to greatly improve healthcare, but it also highlighted the importance of addressing ethical issues and ensuring that AI supports, rather than replaces, human healthcare workers. It has definitely shifted my perspective on AI in healthcare, emphasizing the need for careful and responsible use of AI to ensure that it enhances the human aspects of care.

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Chebrolu, K., Shukla, M., Varia, H., & Cherco, K. (2024, December 12). Health care’s quest for an enterprisewide AI strategy. Deloitte Insights. https://www2.deloitte.com/us/en/insights/industry/health-care/ai-led-transformations-in-health-care.html [Rationale: This article explains how AI is becoming more important in healthcare, encouraging organizations to use it across all areas to improve care, efficiency, and patient results. It also talks about how AI can help make processes smoother and provide more personalized care, while also addressing issues like data security, ethics, and changes in the workforce.]

Elhaddad, M., & Hamam, S. (2024). AI-Driven Clinical Decision Support Systems: An Ongoing Pursuit of Potential. Cureus. https://doi.org/10.7759/cureus.57728 [Rationale: This article discusses Clinical Decision Support Systems, focusing on its uses, challenges, and its potential to better healthcare, which was crucial to understand one of my examples of AI applications in the healthcare industry.]

Faiyazuddin, M., Rahman, S. J. Q., Anand, G., Siddiqui, R. K., Mehta, R., Khatib, M. N., Gaidhane, S., Zahiruddin, Q. S., Hussain, A., & Sah, R. (2025). The Impact of Artificial Intelligence on Healthcare: A comprehensive review of advancements in diagnostics, treatment, and operational efficiency. Health Science Reports, 8(1). https://doi.org/10.1002/hsr2.70312 [Rationale: This article reviews AI's impact on healthcare, highlighting advancements in diagnostics, treatment, and efficiency, while addressing challenges like data security, biased data, and the need for ethical regulations.]

Laliotis, G. (2023, July 26). The Rise of Virtual Health Assistants: Digital Healthcare. Docus.ai. https://docus.ai/blog/virtual-health-assistants [Rationale: This article discusses the rise of Virtual Health Assistants in digital healthcare, emphasizing their role in improving patient engagement and supporting healthcare tasks while addressing concerns about privacy and data security. The article directly mentions Ada Health and provides an overview of its functions/uses.]

Wizard, W. (2023, May 18). Escientia’s AI-Powered drug discovery platform is the future of precision medicine. Seeking Alpha. https://seekingalpha.com/article/4605592-exscientia-ai-powered-drug-discovery-platform-is-the-future-of-precision-medicine?source=acquisition_campaign_google&campaign_id=22007308445&internal_promotion=true&utm_source=google&utm_medium=cpc&utm_campaign=22007308445&utm_term=174345872040%5Edsa-1485125208378%5E%5E724954755785%5E%5E%5Eg&hsa_acc=5428037747&hsa_cam=22007308445&hsa_grp=174345872040&hsa_ad=724954755785&hsa_src=g&hsa_tgt=dsa1485125208378&hsa_kw=&hsa_mt=&hsa_net=adwords&hsa_ver=3&gad_source=1&gbraid=0AAAAACup1Pyj1fvzVpAfGtGjLYr3PnHDY&gclid=Cj0KCQjwytS-BhCKARIsAMGJyzo37EP2C2uJGRnoa8MfoDi7eZBBE04Cu2RnIfhIq4z_lIWGhkNqhQwaAovEEALw_wcB  [Rationale: The article discusses how Exscientia uses AI to speed up and improve the process of discovering new drugs.]