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I chose the healthcare industry for this assignment because it directly impacts people’s lives, and it's always been interesting how science and technology can work together to positively influence healthcare. Artificial Intelligence has become a transformative force in healthcare. Specifically, in helping doctors make faster, more accurate patient care decisions and giving patients better access to this care. From diagnosing diseases to medical imaging to developing new drugs and providing virtual health assistance, AI is largely reshaping the future of medicine and the medical field.

My interest in this industry comes from my life-long interest in medicine. In terms of AI, it is fascinating to see its ability to detect early signs of illness and even assist in surgeries. This shows how technology, such as AI, can extend a person’s life and potentially save countless other lives.

On my Padlet wall, I will explore three major applications of AI in healthcare, these being diagnostic imaging, drug discovery, and AI-powered virtual assistants. I will also discuss future trends and ethical considerations, such as patient privacy and data bias. Additionally, I will explain the societal impacts of AI on employment, equity, and access to healthcare.

Personally, I find the use of AI in healthcare significant because it combines compassion and innovation. Not only is AI about the power of machines and technology but about improving human well-being. I believe that as AI continues to evolve, it will make healthcare more personalized, efficient, and accessible. This will bring us closer to a future where technology strengthens humankind.

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AI is revolutionizing diagnostic imaging through the use of computer vision and deep learning to evaluate X-rays, MRIs, CT scans, and ultrasounds with great precision. Technologies such as Google’s DeepMind Health and IBM Watson can recognize patterns that suggest the presence of cancer, bone fractures and sprains, and neurological issues. This enables quicker and more accurate diagnoses in patient care. This technology reduces human error and aids in the early identification of diseases, influencing patient care. However, issues like data bias, lack of transparency in AI decision-making, and strict regulatory requirements are present. I consider this AI application interesting because AI can identify small indicators that even experienced clinicians may miss, assisting in saving lives with early intervention.

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The application of AI in diagnostic Imaging.

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AI is revolutionizing drug discovery by using machine learning and neural networks to predict molecular drug interactions and pinpoint promising compounds more quickly than conventional methods. BenevolentAI and Insilico Medicine, AI companies, utilize these models to create new treatments for diseases such as cancer and Alzheimer’s. This technology greatly decreases the time and expenses of research while enhancing the precision of drug targeting. However, these methods encounter obstacles such as the requirement for extensive, high-quality data, ethical concerns, and a lack of transparency in AI decision-making. I find this development interesting because it speeds up the transition from research to actual treatments, making worldwide access to medicine.

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Insilico Medicine - 10 Years of AI Drug Discovery Innovation

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AI-driven virtual assistants such as Babylon Health and Ada Health use natural language processing to communicate with patients, analyze symptoms, and recommend care options. These ]systems enhance healthcare access, lessen the burden on professionals, and offer round-the-clock assistance, especially for people who may not have access to a doctor’s office due to lack of transportation or time constraints. However, these virtual assistants encounter obstacles like privacy concerns, restricted precision for complex or rare medical conditions, and dependence on information provided by users. This technology is important because it enhances healthcare accessibility, particularly for individuals in isolated regions or those who struggle to access medical care.

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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 the healthcare field is moving toward greater personalization, and efficiency. Predictive analytics created by AI tools will anticipate the needs of patients, robotic surgeries will be more accurate, and wearable medical devices, such as glucose monitors, will offer continuous real-time health tracking that can aid with patient care. Combining AI with genomics may enable personalized treatment strategies customized to each individual’s genetic DNA, revolutionizing disease prevention and management. However, these AI-dependent developments can lead to significant ethical issues. For example, it is critical to protect patient privacy, especially since AI depends on large amounts of sensitive medical data. It is important to not violate HIPAA. Bias in AI-algorithms can also result in unequal healthcare outcomes, especially for underrepresented groups of people. Additionally, as AI becomes more autonomous in decision-making, problems including accountability and responsibility arise when errors occur. To ensure ethical use, transparent systems, strict data protection laws, and human oversight are essential. Personally, I believe the success of AI in healthcare depends on finding the right balance between technological innovation and ethics. Addressing bias, ensuring privacy, and maintaining human judgment in critical decisions are key to building public trust. It is important to note that errors can cost someone their lives, and in these cases it can be difficult to figure out who is responsible. If used  responsibly, AI has the power to revolutionize healthcare by making it more accurate, accessible, and inclusive for people worldwide.

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AI significantly influences society through healthcare by revolutionizing the diagnosis, treatment, and prevention of diseases while redefining the medicine as a whole. AI in healthcare enhances diagnostic precision, accelerates drug development, and increases the surveillance of public health. However, the use of AI also brings up concerns about job loss as technology takes over certain administrative and diagnostic healthcare positions. Privacy is at significant risk as AI depends on extensive quantities of sensitive patient information, increasing the potential for misuse or violations of this information. Equity poses another challenge. For instance, hospitals in wealthier areas can invest in advanced AI technologies, while underprivileged healthcare systems may fall behind technologically, increasing global inequalities. In spite of these difficulties, AI has the potential to enhance healthcare by increasing access to remote and underprivileged regions, minimizing workloads, and increasing efficiency when used ethically. Nonetheless, improper use, prejudice, or the lack of transparency may decrease patient trust in healthcare organizations. The use of AI in healthcare has both benefits and disadvantages. For instance, it holds significant potential to enhance efficiency, accessibility, and equity in healthcare, but this is dependent on the implementation of strict ethical regulations and data safeguards for patient safety. Ensuring that the general public is understanding and has confidence in AI-controlled healthcare will be crucial to guarantee that AI serves as a benefit for health equity instead of creating more inequalities.

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The research process for this Padlet assignment was successful and fun, however, somewhat difficult. It was somewhat difficult to find specific examples, such as companies that specifically use AI in drug discovery. AI will definitely positively impact healthcare by making medical care more accessible and efficient. Before the start of this course, I was very against regular AI use, however, with the research I have performed over the past few weeks and especially this assignment, I am coming to understand that AI is a powerful tool, especially in healthcare and the advancement of medicine.

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1. He, J., Baxter, S. L., Xu, J., Xu, J., Zhou, X., & Zhang, K. (2019). The practical implementation of artificial intelligence technologies in medicine. Nature Medicine, 25(1), 30–36. https://doi.org/10.1038/s41591-018-0307-0

This reference was used because it discusses how AI is used in healthcare.

2. 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

This reference was used because it talks about how AI is used in healthcare and how it was used in the past, as well as predictions for how it will be used in the future.

3. Longoni, C., Bonezzi, A., & Morewedge, C. K. (2019). Resistance to medical artificial intelligence. Journal of Consumer Research, 46(4), 629–650. https://doi.org/10.1093/jcr/ucz013

This reference was used because it explains the public’s hesitancy towards the use of AI in healthcare and discusses what these concerns are.

4. Dankwa-Mullan, I. (2024). Health equity and ethical considerations in using artificial intelligence in public health and medicine. Preventing Chronic Disease, 21, Article 240245. https://doi.org/10.5888/pcd21.240245

This reference was used because it discusses the ethics and equity concerns of using AI in healthcare.

5. BenevolentAI. (2023). BenevolentAI’s approach to AI-enabled drug discovery. https://www.benevolent.com/news-and-media/blog-and-videos/benevolentais-approach-ai-enabled-drug-discovery/

This reference was used because it talks about BenevolentAI and how it uses AI in discovery medications.