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The healthcare industry provides services and products to keep people healthy, including hospitals, doctors, pharmaceuticals, and insurance. It covers areas like primary care, specialty care, and mental health. The industry is shaped by technology, regulations, and patient needs, with trends like telemedicine and personalized care. It plays a crucial role in society but faces challenges like cost and access. In terms of cost, AI definitely falls into play with using machines to complete simple tasks instead of hiring workers or even with the advancement of technology, pharmaceuticals and manufacturing companies could even appoint machines to produce and come up with medication instead of hiring and seeking help from a real doctor / scientist. Similarly, with the advancement of AI, healthcare could be provided via apps, websites or anything online instead of clinics or hospitals in secluded areas with vast populations.

I chose the healthcare industry because I intend to pursue a career in this industry and would like to research more on how AI has been implemented and will continue to reform the industry. For my wall today, I will be discussing the implementation of AI into the various sections of healthcare and the impacts, pros and cons as well as future trends with them. Personally, my decision to pursue a career in healthcare stems from my attraction towards Neuroscience from a young age. With the advancement of AI, I would definitely love to know more about its implications within the industry and the pros and cons going forward.

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Description : AI analyzes medical images like X-rays and MRIs to detect diseases such as cancer or fractures faster and more accurately than humans.

Technology Used :

Machine Learning

Computer Vision

Deep Learning (especially convolutional neural networks)

Benefits :

More accurate and faster diagnoses

Consistent results

Early disease detection

Reduces doctors' workload

Challenges :

Needs large, high quality datasets

Risk of bias in AI models

Lack of transparency in decision-making

Difficult to integrate into healthcare systems

Privacy and regulatory issues

Personal Insights : I feel like AI in this section of the healthcare system is definitely something that is resourceful and will benefit everyone worldwide however I am also fearful of the possibility of the diagnostics being incorrect for several patients. Would people still want to acquire an education in the industry if all the work can be done by AI. If we do have a stable harmony of human and machine doctors, where do we the draw the line of authenticity of the diagnosis and who could the patients rely on or trust if they need help?

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Artificial Intelligence in Medical Imaging : Koen Van Leemput

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Artificial Intelligence in Medical Imaging : Koen Van Leemput

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Artificial Intelligence in medical imaging: From research to clinical practice – Koen Van Leemput

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Description : Virtual Health Assistants (VHAs) are AI-powered tools (like chatbots or voice assistants) that help patients with tasks such as answering health questions, booking appointments, or managing medications.

Technology Used :

Natural Language Processing (NLP)

Machine Learning

Speech Recognition (for voice-based assistants)

Benefits :

24/7 support for patients

Reduces burden on healthcare staff

Improves patient engagement and self-care

Fast and consistent responses

Challenges :

Limited understanding of complex or emotional queries

Accuracy depends on quality of data and training

Privacy and security concerns

Not a replacement for real medical professionals

Personal Insights : I have definitely seen the implementation of VHAs in healthcare recently and even though they are helpful and efficient to work with, sometimes I would prefer to talk to a human because it feels closer and more dependable. I have experiences circumstances where AI chatbots couldn't provide the same emotional stability as humans in cases of serious questions or inquiries.

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The AI Doctor Is In Exploring Chatbots and Virtual Healthcare Assistants

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Description : Remote monitoring uses AI-powered devices and wearables to track patient health (e.g. heart rate or glucose levels) in real-time, often from home.

Technology Used :

Machine Learning (to detect patterns and predict issues)

IoT (Internet of Things) devices

Data Analytics

Benefits :

Continuous, real-time health tracking

Early detection of health problems

Reduces hospital visits and readmissions

Improves care for chronic conditions

Challenges :

Data privacy and security risks

Dependence on reliable internet and devices

Accuracy and reliability of sensors

Not suitable for all patients (e.g. elderly with technological barriers)

Personal Insights : I feel like this is definitely a beneficial addition to the industry because a lot of times people are unable to visit doctors in person and so having a wearable devices would help to reduce risks of major emergencies. On another note, these devices can be expensive and for people with almost no access to healthcare, these wouldn't really help. I hope in the future, these devices can be affordable by the majority of a population so secluded countries or areas within a country can receive healthcare without having to worry about traveling thousands of miles.

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This Ai Wearable Tech Will Make You Question Reality

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Future Trends with Ethical Considerations

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Future Trends with Ethical Considerations

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AI is rapidly changing how healthcare works, and it's only going to grow from here. In the near future, we will likely see more advanced uses of AI for predicting health issues before they happen. For example, AI could analyze someone's health data to spot early signs of diseases like diabetes or heart problems. Personalized medicine is another big area. AI could help doctors create treatment plans that are tailored to each person's unique needs. We might also see more inclusion of AI in things like virtual assistants, robotic surgeries, and remote monitoring tools, making healthcare more accessible and efficient.

Although these developments sound beneficial and exciting, they do raise some serious ethical questions. A major concern would definitely be privacy. AI systems would need a lot of personal health data to work, which could be misused if not handled properly. Bias is another issue. If an Ai is trained on data that lacks diversity, it might not work well for all groups of people, which could lead to unfair treatment. And of course, there is transparency. Sometimes it's hard to understand how AI makes decisions, which can be a problem in situation where people's lives are on the line.

Overall, AI has the potential to do a lot of beneficial good in healthcare, but it has to be used responsibly. Which means building fair, secure, and understandable systems that would support healthcare workers, not replace them.

Personal Insight : I feel like I definitely agree with the future trends and consideration of ethical use with AI because in present times, most of there future trends are going into effect and if people do not feel secure with AI, the healthcare industry might have to fully cease the usage of AI or come up with better alternatives. As much as we love AI, it can definitely be detrimental, especially in an industry where we have to fight between life and death on a daily basis.

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AI definitely has a big impact in the healthcare industry and is changing it in big ways. One of the biggest concerns surely points towards the effects on employment. As more tasks, like reading medical images or scheduling appointments, become automated, some healthcare jobs may be replaced or redefined. While this can improve efficiency, it also creates a fear of job loss, especially in administrative roles. On the other hand, AI could also create new tech-based jobs that require different skills, shifting the kinds of training future healthcare workers need. Another big issue would be privacy. AI systems rely on large amounts of personal health data to work properly and if that data isn't stored properly or used responsibly, it could lead to serious breaches of trust, especially if sensitive information is leaked or misused. Another slowly growing concern is with equity. AI tools often work best with diverse, high-quality data, but if the data is biased or incomplete, certain groups (e.g. minorities or people in low-income areas) may not get the same quality of care. This could potentially lead to making existing health inequalities worse.

On a broader scale, there are certainly concerns about over-reliance on technology. While AI can support healthcare workers, it's important that human judgment remains central in healthcare decisions. Overall, AI has the potential to make healthcare more accurate, efficient, and accessible, but only if we address the social and ethical issues that it will bring along.

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Before I started working on the different sections of the assignment, I researched about AI in general in the healthcare industry. Then, through the research, I found some connections between multiple articles and decided to use them as my resources for my assignment. Furthermore, I also read articles on google and watched some videos on YouTube for the 3 examples I used because I wanted to learn about them more explicitly and understand the pros and cons, if any.

While researching, I did stumble upon some articles where I could find a clear bias, some towards and some against AI, which really hindered with my evidence because it was affecting the neutrality of the research. I tried to find papers which had a neutral stance and talked about AI in healthcare in general without addressing any personal issues they might have suffered through AI. Another big challenge was finding these papers from credible sources. A lot of the articles and papers that I found to be interesting and worthy of adding to my research often time were not authentic and that led me to a block during the completion of the assignment. I always use the RAVEN method, however, some websites looked very credible and were impossible to determine if it was generated by AI or actually researched and written by a human.

I think AI will definitely be beneficial in the healthcare industry and will lead to much more efficiency and advancement in terms of diagnosis and treatments. However, like I mentioned before, there are surely concerns of certain things with AI and we will need to monitor these tools carefully in order to respect the privacy and benefits of the workers as well as patients. I would love for AI to be used a tool, rather than the ultimate problem-solving machine in the industry. I am also very excited and intrigued to see how far AI will lead to advancements in the industry and what other inventions will make the day of light.

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Impact of Artificial Intelligence (AI) Technology in Healthcare Sector: A Critical Evaluation of Both Sides of the Coin. (2024, January 22). PMC PubMed Central. Retrieved October 16, 2025, from https://pmc.ncbi.nlm.nih.gov/articles/PMC10804900/

(This article talks about AI transforming healthcare by improving diagnosis, treatment, and efficiency, but its success depends on addressing ethical, privacy, and implementation challenges.)

Ellis, L. D. (2024, August 30). The Benefits of the Latest AI Technologies for Patients and Clinicians. Harvard Medical School. Retrieved October 17, 2025, from https://learn.hms.harvard.edu/insights/all-insights/benefits-latest-ai-technologies-patients-and-clinicians

(This article talks about how AI is transforming healthcare by enhancing efficiency, diagnosis, treatment, and decision-making, while encouraging clinicians to adapt and learn its use.)

Thaldar, D., & Bottomley, D. (2025). Correction: Public trust of AI in healthcare in South Africa: results of a survey. BMC Medical Ethics, 26(1). http://dx.doi.org/10.1186/s12910-025-01293-3

(This article talks about AI is transforming healthcare by automating tasks, enhancing diagnosis and treatment, and supporting clinicians in delivering better patient care.)

Mandelia, A., Rengan, V. S., Mehta, A. R., Vankam, A. V., Babu, R., Biswas, S. K., & Agrawal, V. (2025). Artificial Intelligence Use in Daily and Professional Life among Pediatric Surgeons in India: A Roadmap for Adoption Based on Online Survey Results. Journal of Indian Association of Pediatric Surgeons, 30(3), 361+. http://dx.doi.org/10.4103/jiaps.jiaps_306_24

(This article is a national survey of pediatric surgeons in India that revealed growing interest and cautious optimism toward AI integration in clinical and research practice, highlighting the need for targeted training, ethical guidelines, and strategic implementation to fully harness its potential.)

Ralla, B., Biernath, N., Lichy, I., Kurz, L., Friedersdorff, F., Schlomm, T., Schmidt, J., Plage, H., & Jeutner, J. (2025). How Accurate Is AI? A Critical Evaluation of Commonly Used Large Language Models in Responding to Patient Concerns About Incidental Kidney Tumors. Journal of Clinical Medicine, 14(16). http://dx.doi.org/10.3390/jcm14165697

(This article talks about a study that found that Google Gemini provided the most accurate and complete responses to patients about incidental kidney tumors, through all LLMs require cautious use in clinical settings.)

Chustecki M. (2024). Benefits and Risks of AI in Health Care: Narrative Review. Interactive journal of medical research, 13, e53616. https://doi.org/10.2196/53616

(This article highlights that while AI offers significant benefits in healthcare, such as improved diagnostics and efficiency, it also poses risks, including bias, privacy concerns, and lack of transparency, requiring careful oversight for safe implementation.)

https://youtu.be/uvqDTbusdUU?si=0X0RPy8ZSQQ3uNii

(This video talks about the immense potential that AI holds to transform healthcare by personalizing treatment, improving efficiency, and aiding complex diagnoses like cancer, but its effective and equitable implementation is challenged by outdated regulations that inhibit its ability to learn and the critical risk of data bias in training models.)

https://youtu.be/wD1qn2i3Wb4?si=lVZvyyI4wO-jcH0g

(This video talks about AI presenting a powerful opportunity to improve personalized treatment and diagnostic capabilities in healthcare, its effective deployment is severely hampered by outdated regulations that restrict its learning capacity and the persistent risk of bias from non-representative training data.)

Bajwa, J., Munir, U., Nori, A., & Williams, B. (2021). Artificial intelligence in healthcare: transforming the practice of medicine. Future healthcare journal, 8(2), e188–e194. https://doi.org/10.7861/fhj.2021-0095

(This article talks about how AI will fundamentally transform medicine by augmenting human effort to deliver personalized, data-driven, and cost-effective care, but its success relies on responsible, human-centered development and integration into clinical workflows.)

Dhillon, G. M., Grewal, H. M., Buddhavarapu, V. M., Virmani, A., Surani, S. M., & Kashyap, R. M. M. (2024, May 01). Humanity at the Crossroads: Ethical Implications of AI in Medicine. The Hospitalist. Retrieved October 17, 2025, from https://www.the-hospitalist.org/hospitalist/article/36988/hospital-medicine/humanity-at-the-crossroads-ethical-implications-of-ai-in-medicine/#:~:text=The%20use%20of%20AI%20in,communicated%20with%20sensitivity%20and%20empathy.

(This article talks about AI at an ethical crossroads in medicine, where its potential to transform care is challenged by the need to mitigate algorithmic bias, ensure patient consent and autonomy, and preserve the essential human empathy in the patient-provider relationship.)