How AI is Bringing Better Healthcare to Everyone

Artificial intelligence (AI) is quickly becoming a part of everyday life. As a patient, many may wonder how AI will impact the healthcare system. In this article, we compiled recent research on how AI is being used in healthcare systems to improve care and detection of illnesses. 

What is Artificial Intelligence (AI)? 

Artificial intelligence, or AI, is a broad term for computer systems that can learn patterns from data or analyze complex tasks that require intelligence. Using AI in healthcare can improve patient outcomes and how healthcare systems operate by improving diagnostics, automating administrative tasks, and personalizing treatment plans.

How is AI used in healthcare?

According to the European Commission, AI can facilitate the administration of healthcare resources and reduce waste by forecasting patient admissions and the use of hospital facilities, it also has the potential to reduce costs and inefficiencies.

AI can help streamline administrative tasks like patient scheduling, billing, and electronic health records management by automating and optimizing operations. This can free healthcare professionals to focus more on patient care, and reduce burnout of healthcare workers often have over documentation.

In diagnostics, AI enables earlier detection of diseases, even rare diseases that may be overlooked by humans. When diseases are diagnosed early, there is room for less invasive and more cost-effective treatment options.

What is machine learning? 

Machine learning is a type of AI that can learn from data, identify patterns, and make decisions or predictions. These technologies allow processing huge amounts of data and finding complex relationships that might be hard for a person to notice.

AI use in healthcare serves as a digital assistant to help diagnose diseases faster. It looks at a patient's symptoms, laboratory tests, and vital signs to suggest what might be wrong, thanks to pattern recognition. This is called clinical decision support, and it helps healthcare workers make faster and more accurate diagnoses. AI could be especially helpful in rural areas because it can provide specialized medical knowledge through internet access, making it easier for people to get care even if they live far from a hospital.

For example, a recent study found that remote check-ups could help prevent infections in people with blood cancers. This can mark a future in healthcare using AI to prevent disease complications. 

AI needs to be supervised and reviewed by human professionals, not all results are absolute

While AI is a powerful tool for analyzing data, it is not always right, and its conclusions or actions can fail. When used for healthcare, professionals should always double-check the results to ensure patient safety. This is called “human-in-the-loop.” 

A study with over 200 medical workers showed that people often trust AI recommendations even when they are wrong. This is called automation bias. When the AI gave the correct answer, doctors and nurses were ten times more likely to get the diagnosis right. But when the AI was wrong, the medical workers made many more mistakes than they did without AI. This shows that human expertise is still very important. Doctors need special training to look at AI suggestions with a critical eye to make sure the final decision is safe for the patient.

The importance of keeping patient data safe and private, especially when using AI 

To make AI better, it needs to learn from the records of many different patients. In the United States, this is difficult because patient information must be kept very private. Researchers are testing a new method called federated learning. Instead of sending all patient data to one big computer, the AI travels to different hospitals to learn locally. This way, private names and details never leave the hospital where they belong.

There is often a balance to find between making the AI as accurate as possible and keeping the data as private as possible. Using these careful methods helps build trust so that patients feel safe when their information is used to improve medical technology.

For example, HealthTree uses machine learning to do research, as well as human verification. When patients connect their records we make sure their data is secured, and confidential in all research projects.

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Improving healthcare in rural areas

Rural communities often have a hard time getting medical help because there are few doctors and larger hospitals are far away. A recent review found that AI tools can help solve these problems. For example, AI can help local health workers find diseases like tuberculosis or cancer more accurately. 

These tools can be used on mobile phones or through the internet, which means a patient does not always have to travel to a big city for a check-up. However, it is still hard to set these systems up because many small towns do not have fast internet. For AI to work well in these areas, governments need to invest in better technology and train local workers on how to use it.

AI as a legal participant for medical decision-making? 

At the beginning of 2026, Utah launched the nation’s first state-approved pilot program that allows an AI system to legally help make decisions for prescription renewals. This 12-month program uses a platform called Doctronic to approve refills for long-term health conditions like diabetes and hypertension. Patients can request a refill online for a small fee, and the AI verifies their history by checking a shared pharmacy database to ensure the medication was previously prescribed. 

While the goal is to reduce the workload for doctors and make it easier for patients to get medicine, some experts worry about safety risks, such as the AI missing a drug allergy or an outdated lab result. To protect patients, the program follows a "doctor, not device" principle, meaning that any uncertain or complicated cases are immediately sent to a licensed human physician for a final review.

How HealthTree is using AI as a tool to accelerate research

HealthTree is using AI to accelerate research and improve patient outcomes. Our research uses AI as a tool to match patients with clinical trials, analyze real-world data from electronic health records, and predict disease progression. While we still rely on human power to verify all data is correct and have polished results, AI has been a tool that has helped accelerate research that brings us closer to a cure. 

Create your account to become a cure contributor, there are many ways to help, from donating, to connecting your records or answering patient surveys, it all helps. 

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AI technology in healthcare is a powerful tool that can help more people get the medical care they need, regardless of where they live. It works best when it supports doctors rather than replacing them, as humans are needed to catch occasional machine errors. By using new ways to train these systems, we can make medicine more accurate while still protecting the private details of every patient. As these tools continue to grow, the goal is to create a healthcare system that is fair and reliable for everyone.

Sources: 

• Artificial Intelligence in healthcare
• Impact of AI recommendation correctness on diagnostic accuracy in clinical decision-making
• Implementation of AI-Driven Diagnostic Tools to Improve Access and Efficiency in Rural Healthcare: An Umbrella Review
• Artificial Intelligence in Internal Medicine: A Study on Reducing Diagnostic Errors and Enhancing Efficiency
• Machine Learning in Healthcare
• Utah Becomes the First State to Permit AI ‘Decision-Making’ Authority for Prescription Renewals