# data[].attributes.body
There is no way to know what the future holds for AI in the healthcare industry. However, we can look at trends and patterns to make assumptions about the future of AI in healthcare. One possibility for the future is further involvement in AI patient management. In the future AI may handle patient consultation and extract information from patient’s electronic footprint and compose an electronic summary letter for clinicians to approve or disapprove. Since this technology would be used as a tool for clinicians and help save valuable time, rather than replacing them, it is a huge possibility we may see this technology come to life in the near future. Another trend that can be expected in the future is the use of AI when it comes to bringing specialist diagnostic expertise into primary care, as AI can provide instant analysis.

Although AI provides numerous benefits when it comes to the healthcare industry, there are ethical concerns that need to be acknowledged. Data privacy is a huge ethical concern that comes with AI involvement in the healthcare industry. For example some networks gather and store large amounts of patients data, like a patient’s mental health data, without consent from the individuals. Furthermore, our current laws are not enough, as they don’t protect an individual’s health data. This allows companies to do things and store our data almost wherever without our knowledge or consent.

Although I believe incorporating AI in healthcare benefits us immensely, I believe stronger laws, rules, and regulations need to be developed to progress with AI involvement in industries. For one I think companies need to be transparent with patients and provide consent forms to store and analyze data with AI. I also believe companies should notify patients immediately if their data is leaked immediately. Although there are many ethical concerns we need to overcome to merge the world of AI and healthcare, I feel that stronger laws and regulations on AI in the healthcare industry could be beneficial and manageable.

# data[].attributes.body
A huge part of AI diagnostic imaging is machine learning and computer vision. These technologies are used to analyze medical images like X-rays, MRIs, and CT scans. These technologies are more effective than traditional ways as AI algorithms are able to detect various abnormalities such as tumors, fractures, and even infections accurately. In some cases radiologists miss these signs, making AI in diagnostic imaging highly effective. The technology used for Diagnostic Imaging is machine learning and computer vision. There are numerous benefits of incorporating AI in the healthcare industry. Some of these benefits are diagnostic accuracy, reduction of human error, and time efficiency. There are many challenges that arise from AI in healthcare. Those challenges include the fact AI needs large amounts of data to be effective, AI is not always accurate, and more.

# data[].attributes.body
AI plays a huge part in the healthcare industry in many ways. One way AI is utilized in this industry is in predictive analytics. Incorporating AI in this way allows medical professionals to analyze various amounts of data from electronic health records.  Through this process, AI can detect and predict risks like heart disease and diabetes based on patient data patterns. The technology used to achieve this is Machine learning and predictive modeling. There are many benefits of using AI in predictive analytics as AI can detect diseases early on, allowing crucial preventative measures to be put in place, and helping patients get treated and prepared. Although there are many benefits there are some challenges when it comes to using AI in predictive analytics as data needs to be of a certain quality and quantity, patient privacy is also a factor, and in some cases, AI can be inaccurate.

# data[].attributes.body
The topic I have chosen to focus on is the Healthcare industry and how the role of AI is changing the industry. The healthcare industry impacts everyone making it essential to acknowledge and learn about the role of AI in the industry. My choice is due to my passion for healthcare and my drive to become a part of the industry. There are many obstacles in the healthcare industry, many being unexpected. Some of these obstacles are high costs, time, efficiency, limited access to care, improved outcomes, etc. Artificial intelligence has provided solutions to many of these obstacles and has helped save numerous lives in the process.

AI has transformed the healthcare industry in various ways. Some include improving diagnostic accuracy. Another way in which AI has impacted the healthcare industry is that AI is now used to analyze medical images and detect diseases early.  AI is also used in treatment planning and can help make personalized treatment plans. AI is used in other ways in the healthcare industry which will be incorporated in this Padlet.

In this Padlet I will explore the various AI technologies that have changed the healthcare industry. Not only that but I will also touch on future trends, ethical concerns, and the societal impact of these technologies that are now incorporated in the healthcare industry.

# data[].attributes.body
Another huge AI movement within the healthcare industry is virtual health assistants. AI-powered health assistants use natural language processing also known as (NLP) to interact with users. Virtual health assistants help users with medical advice, scheduling appointments, giving solutions to patient’s symptoms,  medication reminders, and more. There are copious amounts of benefits of AI-powered virtual health assistants like reducing waiting time, timely medical advice, healthcare accessibility, scalability, anonymity, scalability, and more. However, there are also many challenges when it comes to these assistants like their inability to help with complex medical issues, reliability, and more. The technology used to power these virtual health assistants is natural language processing and machine learning.

# data[].attributes.body
The involvement of AI in healthcare is revolutionary and will change how the healthcare industry operates. Not only that but it can change how patients engage with the healthcare industry. Another concern is job displacement. Since AI is now used in data analysis, diagnostic imaging, and patient management many are afraid they’re going to lose their jobs due to these new advancements. Although many people in these positions are worried about their jobs, there are new opportunities that come along with the advancements of AI. For example, there are new job opportunities like AI oversight, data analysis, and healthcare technology management.

Another huge concern is privacy, which I talked about in the last section. As I previously mentioned, the storage of patient data and its use doesn’t require a patient’s consent due to the lack of rules and regulations regarding AI. This concerns a vast majority of society as they don’t know how or where their storage is getting used or stored. Additionally, there have been many cases where people’s data has been leaked and they weren’t informed immediately. This is another huge concern to the public as it can have drastic effects on people’s lives.

Another issue presented by the involvement of AI in healthcare is the issue of equity. Due to unintentional bias that could be enhanced by AI, it could hinder the equity of healthcare. Since AI needs large quantities of data it’s possible that AI could amplify bias and amplify racism and more. This issue worries a vast amount of the public as it could lead to unequal care or access to care. There are many concerns when it comes to AI in healthcare, however if stronger laws are made, Ai has the opportunity to change healthcare for the better.

# data[].attributes.body
Through the research I conducted for this assignment, I gained a deeper understanding of its impact and potential to change the healthcare industry. I faced a few challenges through my research but was able to overcome them. One challenge I faced was choosing examples of AI technology in healthcare. I had a hard time focusing on 3 specific AI technologies used in healthcare as there were so many options to choose from. To overcome this challenge I had AI choose 3 options out of the options I provided. I believe the incorporation of AI in the healthcare industry can change the healthcare industry for the better and make healthcare more accessible and efficient.

# data[].attributes.attachment_caption
I wasn't able to do a video recording, so I chose to go with an audio recording. However, I understand if I receive a deduction in points.

# data[].attributes.body
National Center for Biotechnology Information. (2022, December 1). Artificial intelligence in healthcare: The role of virtual health assistants. PubMed Central (PMC). https://pmc.ncbi.nlm.nih.gov/articles/PMC11140094/#:~:text=In%20particular%2C%20VHAs%20can%20struggle,spectrum%20of%20individual%20health%20scenarios. This website is reliable and provides great detail about the role of Ai-powered virtual health assistants.

National Center for Biotechnology Information. (2020, March 1). Artificial intelligence in health care: An essential guide for clinicians. PubMed Central (PMC). https://pmc.ncbi.nlm.nih.gov/articles/PMC8826344/

This website is reliable and goes in-depth about ethical concerns surrounding AI in healthcare.

National Center for Biotechnology Information. (2017, September 5). Artificial intelligence in healthcare: Past, present and future. PubMed Central (PMC). https://pmc.ncbi.nlm.nih.gov/articles/PMC5819974/

This source has valuable information regarding future trends regarding AI in healthcare.

National Center for Biotechnology Information. (2020, February 21). Artificial intelligence in healthcare: Review and prediction of outcomes. PubMed Central (PMC). https://pmc.ncbi.nlm.nih.gov/articles/PMC7486549/

ForeSeeMed. (n.d.). Predictive analytics in healthcare. ForeSeeMed. Retrieved March 16, 2025, from https://www.foreseemed.com/predictive-analytics-in-healthcare

Prainsack, B., & Rabenau, M. (2021). Ethical challenges in AI in healthcare. BMC Medical Ethics, 22(1), 1-10. https://doi.org/10.1186/s12910-021-00687-3