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AI applications play a crucial role in transforming the healthcare industry, where healthcare systems can see an improvement in diagnostics, treatment, and patient care due to the use of AI technology. The possibilities of AI application in the healthcare system are endless and constantly improving. Ultimately, AI enhances decision-making, improves outcomes, and increases the accessibility to quality healthcare. I decided to choose the healthcare industry because although I am not a pre-med major, I am very fascinated my human genetics and genomics and as a Human Evolutionary Biology Major with a focus on human genetics and genomics, I find interest in this industry because of their research and work with genetic material and genetic diseases. I know the importance of researchers who are working tirelessly to research genetic material to help improve the healthcare systems as well as societal welfare. I will be covering 3 specific AI applications in the healthcare industry; medical imaging and diagnostics, personalized medicine and treatment plans and predictive analytics and early disease detection. The healthcare industry and AI applications within it are significant to me because I want to do extensive research on human genetics. Scientists who research human genetics and genomics work closely with those in the healthcare industry. A lot of research, geneticists collect, is data that is critical for others in the field because they need that data in order to work on and improve medical treatments, devices and medicine used to help the welfare of millions of patients around the world.

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In medical imaging and diagnostics, AI applications focus on analyzing medical images (like X-rays, CT scans, and MRI’s) to detect abnormalities and assist in disease diagnosis. The primary AI technology used in medical imaging & diagnostics is deep learning, specifically convolutional neural networks (CNNs) where it learns to detect features in input data. The ai technology identifies patterns and subtle changes which ultimately improves diagnostic accuracy which is powered by deep learning.

The NYU Langone’s Department of Radiology is doing extensive research with the use of AI to transform medical imaging. “In 2018, we publicly released the fastMRI Dataset- the largest open-source collection of deidentified MRI data for research into AI-driven image reconstruction” (Artificial Intelligence in Biomedical Imaging, n.d.). Their research and use of AI benefits the medical industry by making MRI faster and more accessible, detect breast cancer more accurately, better classify neurological issues and detect diseases, such as Alzheimer's far in advance.

Although AI applications have had huge benefits that doesn’t take away from the many complications of early application. “Besides the model expansion restrictions imposed by the limited computing power, training these networks with multiple layers was also challenging” (Pinto-Coelho, 2023). Initial setup of the ai technology proved to be rather difficult and costly, however through technological innovation, things have seemed to improve and become easier to implement.

I find the use of AI application in medical imaging and diagnostics really interesting because it can detect abnormalities a lot quicker than us human beings. It is a really great use of AI because then the patient can be attended to and receive proper care quicker.

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Machine Learning For Medical Image Analysis - How It Works

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AI has transformed personalized medicine by analyzing patient data, including genetic profiles, meant to create tailored treatment plans. Machine learning and deep learning algorithms help identify patterns and predict outcomes, which then aids in drug development. The use of AI has been very beneficial since it creates customized treatment plans based on patient data and leads to faster drug development, which enables a more efficient delivery of healthcare to the patient. However, there are some complications which include; biases in the algorithms, high implementation costs and the potential for over-reliance which affects critical decision-making. Although these are all important complications I think that biases in the algorithms could be most harmful to the industry and the patients themselves as biases can impact the way a patient is treated.

The use of AI in personalized medicine and treatment has aimed to improve patient outcomes by providing targeted treatments that are safe and more effective. “AI has emerged as a valuable tool in advancing personalized treatment, offering the potential to analyze complex datasets, predict outcomes, and optimize treatment strategies” (Alowais et al., 2023)

A really interesting conversation comes up with the use of AI and medical devices. AI and machine learning can be useful for precision medicine. Medical devices with embedded AI technology can be turned into wearable and implantable devices. “We could then use the devices to predict problems or detect dangerous conditions” (Ask a Caltech Expert: AI for Personalized Medicine, n.d.)

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How will AI transform precision medicine? – Ava Amini

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Predictive Analytics & Early Disease Detection

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Predictive Analytics & Early Disease Detection

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AI technologies such as machine learning and natural language processing also play a role in predictive analytics and early disease detection. The machine learning algorithms are meant to analyze patient data, their medical histories and genetic information which is all used to identify patterns and potential risk factors for disease such as cancer or diabetes. The natural language processing further helps to interpret medical data, such as doctors’ notes or research articles, to enhance diagnostic accuracy. These AI applications allow for healthcare professionals to intervene earlier and improve patient outcomes and their treatment efficacy. AI is beneficial in this case by allowing a quicker ability to process vast amounts of data to accelerate research and innovation; however, there is an outstanding challenge of biases in the algorithms due to incomplete or skewed training data, which raises concerns about accuracy and fairness.

There was a study back in 2017 that involved patients with a risk for stroke and healthcare professionals used AI algorithms to place these patients into an early detection stage. “The study found that the early detection alert from the algorithm provided 87.6% accuracy in diagnosis and prognosis” (Dedelaite, n.d.).

The use of AI in early disease detection is huge. The possibilities are endless as new AI algorithms, technology and devices can detect a wide variety of diseases. “Companies like ReptiSpec and Mediwhale are using quick standard eye scans to detect cardiovascular, kidney and eye diseases as well as signs of neurodegeneration” (Early Disease Detection: 3 Tech Trends to Watch | AHA, 2025).

I think that in the world we live in now it’s easy to forget that despite all this technology there are still many diseases that don’t have effective treatments and are very difficult to manage. Technology has come so far and especially in my generation we have grown up using technology throughout middle school and high school and now throughout our undergraduate years. We all have something waiting dormant inside of us and we won’t necessarily know how devastating the effects can be until it has already happened. This is why I find the use of AI to help aid in early disease detection to be incredible. I can’t help but imagine the amount of lives that can be saved from physical and emotional pain by being able to catch disease early before it causes irreversible damage.

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Work on Research Projects On AI ML in Early Detection of Diseases #ai #ml #research #disease

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Artificial Intelligence is being used to revolutionize the healthcare industry, bringing transformative advancements that promise improved patient outcomes and efficiency. One of the most anticipated trends is the expansion of AI-powered diagnostic tools. These systems, often enhanced by machine learning, can analyze medical imaging, detect diseases like cancer at earlier stages, and recommend treatment options with remarkable accuracy. Virtual health assistants and chatbots are also on the rise, providing patients with 24/7 health monitoring and reducing the burden on healthcare providers.

However, these advancements bring ethical considerations that demand attention. Patient data privacy is a top concern, as AI systems often require access to sensitive health information. Ensuring robust data encryption and adherence to privacy laws will be vital. Bias in AI algorithms also poses a significant challenge; these systems must be rigorously tested to prevent disparities in healthcare delivery especially if patient situations are a matter of life or death. As AI takes on greater decision-making responsibilities, accountability becomes critical. Establishing clear protocols for when and how AI is used will be essential to maintaining trust between patients and providers.

The healthcare industry is essential for the welfare of society. Back then, there wasn’t a lot of knowledge and research occurring for sick individuals who were in dire need of help and access to medication. In some instances, medication for diseases didn’t even exist which led to thousands of people being secluded from their families and eventually lost their lives. Technology and extensive research has allowed for medication to be created and tested so that sick individuals have a chance of getting the help they need to live a better life. AI technology is now the next step forward in the healthcare industry. There are still many genetic diseases that have no cure and no medication to help ease the suffering. AI technology is going to help speed up the research process and allow for more data to be collected. It will help lead to more efficient diagnosis and medication to be developed quicker than ever before. It’s a great thing in my opinion.

I think an interesting argument is that some people think that this use of technology is keeping us human beings alive way longer than we should be. I don’t view the use of AI technology in the healthcare industry to be involved with this argument. This technology is going to help so many individuals with genetic diseases that aren’t necessarily preventable and help get them treatment and medicine they need so that they can have a better chance for a more appropriate style of living that they deserve, where they aren’t in as much pain on a day to day basis.

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Artificial intelligence is revolutionizing the healthcare industry by bringing transformative potential yet raising important considerations. By automating administrative tasks, analyzing medical data, and assisting with diagnostics, AI enhances efficiency and precision. However, its rapid adoption has broader implications for employment, privacy, and equity.

In terms of employment, AI-driven automation may displace certain roles, particularly in areas like data entry, medical imaging analysis, or appointment scheduling. While this could lead to job loss for some, it also creates opportunities for new roles in AI development, management, and maintenance. The healthcare workforce must adapt to new technology in order to remain relevant and knowledgeable in this new landscape.

Privacy concerns emerge as AI systems rely on vast amounts of sensitive patient data to function effectively. The risks of data breaches and unauthorized access are heightened, potentially exposing individuals' health information. Striking a balance between the use of data for AI advancements and safeguarding patient confidentiality requires attentiveness.

Equity in healthcare is another pressing issue. AI systems, if trained on biased datasets, can inadvertently continue disparities in care by favoring certain populations over others. Addressing this demands careful development, monitoring, and correction of algorithms to ensure equitable access. Moreover, underprivileged communities may lack access to advanced AI technologies, further widening the healthcare gap.

Although I think the use of AI in healthcare is intriguing and beneficial to many, I am also concerned about the potential negative impacts that it can have on society. With more use of technology and AI in healthcare that leaves many patients sensitive data available to cybercriminals. If that sensitive information gets into the wrong hands, that is a huge violation of patient privacy. I still think that even with the risks it is worth it to integrate AI technology into the healthcare industry. I think we need to keep in mind that there is always room to improve these algorithms and take precautionary steps in order to safely keep patient data and use AI as responsibly as we can.

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Throughout my research process I learned a lot about the many implications that AI technology has had on the healthcare industry. Honestly, its implications shocked me because I had no idea just how much AI has expanded in the industry. There were many more applications than the ones that I have decided to discuss which were outstanding to see. I felt the need to write about AI applications in medical diagnostics & imaging, personalized treatment & medicine, and early disease detection because those were the most intriguing to me and some of the more involved scenarios where we see the use of AI become more useful and prevalent. I think that the use of AI in the healthcare industry, once we efficiently train AI algorithms more, is going to bring the healthcare industry to the next level and more people can get the help that they deserve. My research has shown me that AI can be used for not only good but that AI can be used to improve already existing systems and industries in the world.

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“Alowais et al., (2023). Revolutionizing healthcare: the role of artificial intelligence in clinical practices. BioMed Central. [Rationale: This article provides overview of AI application in the healthcare industry.]”

“American Hospital Association, (2025). Early Disease Detection: 3 Tech Trends to Watch. [Rationale: This article provides an overview on growing trends of AI in the healthcare industry.]”

“Caltech, (2025). Ask a Caltech Expert: AI for Personalized Medicine. California Institute of Technology [Rationale: This article provides insight on AI application in personalized medicine.]”

“Dedelaite, (n.d). The role of AI in early disease detection. Echelon Health.[Rationale: This article provides overview of AI applications in major disease areas.]”

“NYU Langone Health, (2025). Artificial Intelligence in Biomedical Imaging. NYS Grossman School of Medicine. [Rationale: This article discusses what AI research is and what research is currently being conducted.]”

“Pinto-Coelho, L. (2023). How Artificial Intelligence Is Shaping Medical Imaging Technology: a Survey of Innovations and Applications. Bioengineering. [Rationale: This article provides insight on how AI technology is shaping the process of medical imaging.]”