Medical imaging plays a critical role in diagnosing diseases of the brain, but reading and interpreting brain scans is a complex and time‑consuming task.
Today, millions of brain MRI scans are performed around the world each year to look for strokes, bleeding, tumors, infections, and other neurological conditions.
These scans are usually reviewed by highly trained radiologists and neurologists, but growing demand has placed enormous pressure on health systems. In many hospitals, patients may wait hours, days, or even longer to receive results, which can delay treatment and worsen outcomes.
A new study from researchers at the University of Michigan suggests that artificial intelligence could help solve this problem. The research describes an AI-powered model that can analyze a brain MRI and provide a diagnosis in just seconds.
According to the study, the system was able to detect neurological conditions with accuracy as high as 97.5 percent and could also predict how urgently a patient needed medical care. The findings were published in the journal Nature Biomedical Engineering.
The AI system, called Prima, was developed by a team led by Dr. Todd Hollon, a neurosurgeon at University of Michigan Health and an assistant professor at the University of Michigan Medical School.
Hollon and his colleagues created Prima to address a growing challenge in modern medicine: the rising demand for MRI scans and the limited number of specialists available to interpret them.
Brain MRI scans are highly detailed and contain vast amounts of information. Reading them accurately requires years of training and careful attention. Even experienced specialists can be overwhelmed by the increasing number of scans they must review each day.
In emergency situations, such as a suspected stroke or brain hemorrhage, time is especially critical. Delays in diagnosis can lead to permanent brain damage or death.
Prima was designed to assist doctors by rapidly analyzing MRI scans and highlighting the most important findings. The research team tested the system on more than 30,000 MRI studies collected over a one-year period.
Across more than 50 different neurological diagnoses, Prima consistently performed better than other advanced AI models currently used in medical imaging.
One of the most important features of Prima is its ability to assess urgency. Some brain conditions require immediate treatment, while others can safely wait.
Prima was able to identify high‑risk cases and automatically alert the appropriate specialist, such as a stroke neurologist or neurosurgeon, as soon as the scan was completed. This could help doctors act faster and prioritize patients who need urgent care.
Unlike earlier AI systems, Prima does not focus on just one narrow task. Many previous models were trained to detect specific problems, such as tumors or signs of dementia, using carefully selected sets of MRI images.
Prima takes a much broader approach. The research team trained it on every available brain MRI performed at University of Michigan Health since radiology records became digital. This included more than 200,000 MRI studies and over 5.6 million individual image sequences collected across several decades.
In addition to images, Prima also processes written information. The system was trained using patients’ medical histories and the reasons doctors ordered the MRI scans in the first place. This allows Prima to analyze brain scans in a way that more closely resembles how human radiologists work.
Doctors do not look at images in isolation. They consider symptoms, medical history, and clinical context when making decisions. By combining image data with text-based information, Prima gains a more complete understanding of each patient’s situation.
Researchers say this design is a major reason why Prima performed so well across a wide range of conditions. It allows the system to move beyond simple pattern recognition and toward more meaningful clinical reasoning. In effect, Prima acts like a digital assistant that supports doctors rather than replacing them.
The need for such tools is growing rapidly. Neurological diseases are a major cause of disability worldwide, and MRI scans are essential for diagnosis. However, many regions face shortages of trained neuroradiologists, particularly in rural or under-resourced hospitals.
In these settings, patients often experience long delays while scans are sent elsewhere for review. An AI system that can provide fast and reliable information could significantly improve access to care.
Despite its strong performance, Prima is still in the early stages of evaluation. Researchers emphasize that it is not yet ready for widespread clinical use without further testing. Future work will focus on integrating even more patient data from electronic medical records to improve accuracy and reliability. The goal is to mirror real clinical decision-making as closely as possible.
The team also sees broader potential for this technology. Prima’s design could be adapted to analyze other types of medical images, including mammograms, chest X-rays, and ultrasound scans. In this sense, researchers describe Prima as a general assistant for medical imaging, similar to how language-based AI tools assist with writing or problem-solving.
When reviewing the study’s findings, the results are impressive but should be interpreted carefully. The high accuracy and speed suggest that AI can meaningfully support medical imaging workflows, reduce delays, and help prioritize urgent cases.
However, the system was trained and tested within a single health system, which means its performance must be validated in other hospitals and populations. Real-world use will also require careful oversight to ensure safety, fairness, and transparency.
Overall, the study highlights how artificial intelligence, when thoughtfully designed and clinically informed, can enhance rather than replace medical expertise. Prima shows promise as a powerful tool that could reduce workload for doctors, speed up diagnoses, and improve patient outcomes.
As health systems continue to explore how best to integrate AI into care, technologies like Prima offer a glimpse of a future where faster and more accurate diagnoses are available to more people, regardless of where they live.
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