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I chose the medical field because this is the field of work my mom is in and has been in my whole life. From a second-hand experience of it, this is one of the most challenging, gruesome fields of work out there. Long hours, lots of stress, and the need to be on your toes at all times and thinking quickly are all aspects of the job. When presented with this assignment, my biggest question was how artificial intelligence and new technology are being used to benefit people and make positive outcomes more common. From past experiences, I know that minor improvements have already made huge impacts and helped patients. That's what makes AI intriguing to me and more meaningful.

The three examples I will provide will include the topics of diagnostic imaging, personalized medicine, and patient monitoring. They are all topics that AI is impacting in healthcare today. From being a helping hand to doctors making decisions faster and more accurately than ever before, to long-term health monitoring. I will also include: the trends, ethical concerns with the use of AI, and other broader implications and things to consider when using AI in healthcare. But, most importantly to me, in the use of AI in the healthcare field as an aid to healthcare, not a complete replacement for humans. I want to look at both positive and negative effects of the use to more clearly understand how we can apply this safely and efficiently, while not ignoring the risks.

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Example 1 – Diagnostic Imaging (IBM Watson)

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Example 1 – Diagnostic Imaging (IBM Watson)

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AI has started to assist in the operation of CT, MRI, and X-ray scans, helping radiologists flag potentially harmful tumors or fractures. AI is used to have a better understanding of the use of algorithms and help take care of patients more effectively (IBM Newsroom, 2021). An example of this is IBM Watson, which gives the clients a quicker route to solutions with accuracy using a variety of algorithms all in one place. This has the fastest results with reduced risk of error. But, like any AI, one of the biggest concerns is biases and in this case, that can include in databases, which would potentially steer medical professionals in the wrong direction and make the wrong decision. I am interested in this topic because it can help medical professionals, such as my mom, to be accurate and effective when taking care of patients.

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Example 2 – Personalized Medicine (Tempus)

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Example 2 – Personalized Medicine (Tempus)

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Tempus is a company that is utilising AI in the treatment of cardiovascular diseases and cancer. It uses algorithms that utilize genomic sequencing, electronic health records, and machine learning models to narrow in on the best therapies for patients (Tempus AI). Using these systems optimises efficiency while minimising waste in terms of medication. The biggest challenges with this technology are getting the outreach accessible to patients. This type of technology needs training across the board and can be a costly tool, making it difficult for people to have access to it. I feel that this example highlights the importance of taking away the one-size-fits-all model and taking data to personalize a patient's individual needs, making it the future of medicine. This is where I feel the modern healthcare world should be heading.

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Tempus OS | The operating system for precision medicine innovation

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Example 3 – Patient Monitoring (Medtronic)

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Example 3 – Patient Monitoring (Medtronic)

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Medtronic developed AI to identify early warning signs of heart valve disease in at-risk patients. Teaming up with Tempus, they created an algorithm that uses sensor and electronic health record (EHR) data to detect early signs and point doctors toward effective prevention (MedTech Dive, 2024). This technology not only detects issues before they even occur, and starts treatment before there is an actual problem. But, also prevents costly treatments down the line and prevents issues before they can really become a problem. Challenges with this and other monitoring AI include the privacy and data-security concerns and alert fatigue for clinicians. I feel that this example shows another potential upside in healthcare. The key is being proactive and tackling the problem early rather than reacting when something is truly a threatening problem. This has better outcomes and reduces stress of people like my mom in the healthcare field.

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Informa Markets - Engineering Media Brands

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How Medtronic Is Transforming Patient Care with AI

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Over the next decade, healthcare and AI are most likely to advance through federated learning(allowing hospitals to train models on their data without sharing it), explainable AI to better account for machine reasoning, and through a broader implementation of predictive analytics that can draw upon imaging data, genomic data, and wearable device data. Hospitals are starting to adapt and get new systems to make better use of AI and be able to run different models together at the same time.

Ethical concerns are a very hot topic in AI, not just in the medical field. Privacy has always been the main concern with handling patients' private data and information.  One single breach in the system could affect a patient for life, having lasting consequences. The second concern is with having biases. AI is based on data sets, so if the data set is, for example, male-dominant patient databases, they are most likely not going to work as well for anyone outside those parameters. The Third aspect is having transparency with patients and holding people accountable. Both the medical professional and the patient should know and be aware of why the algorithm is making the decisions they are making. Consent policies and having good oversight of these programs will need to be updated with the new technology emerging.

In my opinion, the two biggest focuses need to be fairness to everyone and good human oversight with this new technology. I feel that AI should be used as a valuable tool when it comes to AI, but not completely take over human insight and judgment. The most exciting part to me is to be able to see this futuristic technology being provided to everyone and be able to be transparent with the medical professionals and with patients. Being able to provide detailed insight into their results and let there be checks and balances with human insight. The biggest potential risk is for the commercialization of AI, which skips necessary safety protocols or has no oversight. In short terms, this means very quick results and profit over safety for the patients. The standard that they hold this emergence in technology will define whether AI lives up to its true potential or becomes a major issue that creates new problems and inequalities.

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AI, despite being a helpful tool to use, has also had its impacts on society. While it can cut their work and effort into just half the time, it is also replacing entry-level jobs. It can do tasks such as image analysis, paperwork, and data entry. On the flip side of that, there are more jobs opening up as AI specialists, data scientists, and clinical ethicists in this field. Hopefully, going into the future, healthcare professionals have a positive relationship with AI, allowing them to use it as an assistant and focus more on the harder, more complex cases

Privacy is the first and most important risk in talking in terms of AI. As we have seen in the past, data systems aren't the most secure when getting into our banking systems and phones. So making sure we have top-notch encryption on these systems will be crucial in protecting patients' confidentiality.  Without this information could be used against individuals and misused, having lasting lifelong consequences ranging from discrimination to denial of coverage.

In discussing the implementation of these systems in hospitals, one issue is the financial aspect. The larger hospitals with the largest budgets will continue to thrive and advance, leaving behind the smaller, more rural clinics that can't afford to keep up with new technology and the large price tag. Having public insight and government aid will help with this off-balance. They should ensure that everyone has access to these trainings in the new technology and that AI in healthcare is accessible to all and affordable

Gaining society's trust in this new technology is the make-or-break of this technology. Public image is everything, especially in the field of healthcare. If people start to feel as if the technology makes too many errors or its reasoning doesn't really support the answer, they will begin not to trust it, eliminating it from use. With this, AI can help improve human-to-human care rather than completely replacing them, and give them more consistent quality care, which is what society needs.

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From this research on how AI has impacted the healthcare system. This has been a topic I have started to think about more as it becomes more prominent in our society. It makes stressful jobs like my mom's make important decisions quicker and more accurately than ever before. The most difficult part of this research is finding good, credible resources, but the result has been worth the effort to have a better understanding of what is going on in the world of healthcare. It has helped me see the value in technology and how it can impact the human care experience.

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1. IBM Newsroom. “IBM Watson Health Introduces New Opportunities for Imaging AI Adoption.” IBM Newsroom , 30 Nov. 2021, https://newsroom.ibm.com/2021-11-30-IBM-Watson-Health-Introduces-New-Opportunities-for-Imaging-AI-Adoption.

Rationale: This primary source from the official IBM website directly and clearly explains how Watson Health is using AI in the specific context of diagnostic imaging, which will give you strong, reputable context for Example 1.

2. Tempus Labs. “AI-Powered Precision Medicine for Oncology and Cardiology.” Tempus Official Website , 2024, https://www.tempus.com/.

Rationale: This is a primary source that directly and simply explains how Tempus uses AI and machine learning for precision medicine, which will support your Example 2.

3. MedTech Dive. “Medtronic, Tempus Testing AI to Find Potential TAVR Patients.” MedTech Dive , 7 Nov. 2024, https://www.medtechdive.com/news/medtronic-tempus-ai-trial-tavr/733845/.

Rationale: This recent and reliable article describes the joint testing between Medtronic and Tempus that will use AI to help identify people with heart disease earlier, which will support your Example 3.

4. Medtronic Newsroom. “Medtronic Begins Multicenter Study to Address Health Disparities in Structural Heart Disease Care.” Medtronic Newsroom , 12 Nov. 2024, https://news.medtronic.com/Medtronic-begins-multicenter-study-to-address-health-disparities-in-structural-heart-disease-care.

Rationale: This is official information from Medtronic on its specific AI-driven equity research, which will be useful for your “Societal Impact” section.

5. IBM Think. “What Is Artificial Intelligence in Medicine?” IBM Think Blog , IBM, 2024, https://www.ibm.com/think/topics/artificial-intelligence-medicine.

Rationale: This is a clear and comprehensive explanation of AI’s use in medicine that comes directly from IBM, which will support your “Personalized Overview” and “Future Trends” sections.

6. Faiyazuddin, M., et al. “The Impact of Artificial Intelligence on Healthcare.” National Library of Medicine (PMC) , 2025, https://pmc.ncbi.nlm.nih.gov/articles/PMC11702416/.

Rationale: This is a scholarly, peer-reviewed academic study that offers an evidence-based perspective on the specific benefits, challenges, and ethics of AI in modern healthcare.