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Home»ADOPTION NEWS»AI drive MRI analysis reveals high accurate stroke precursors.
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AI drive MRI analysis reveals high accurate stroke precursors.

By Crypto FlexsMay 24, 20252 Mins Read
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AI drive MRI analysis reveals high accurate stroke precursors.
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Felix Pinkston
May 23, 2025 10:32

A new study shows that AI technology is able to prevent stroke through initial detection by enabling the identification of atrial fibrillation in the brain MRI.





Artificial intelligence (AI) is revolutionizing in the medical field by providing new ways to prevent stroke. According to NVIDIA’s articles, researchers have developed an AI model that can analyze everyday brain MRI and identify atrial fibrillation (AFIB), a general pioneer of stroke.

AI model for early detection

In a study published in the Journal of Cerebrovascular Disease, scientists from the Royal Melbourne Hospital introduced a deep learning model that detects AFIB by recognizing subtle patterns in the MRI scan. The neural network called Condnext was trained for MRI in 235 stroke patients and achieved 84%impressive accuracy when distinguishing stroke by AFIB caused by other factors.

The importance of AFIB detection

Atrial fibrillation is a major cause of ischemic stroke, which accounts for almost 90%of all stroke cases. The ability to detect AFIB early can significantly reduce the incidence of these strokes. Bernard YAN, a professor of Royal Melbourne Hospital and a neurologist, emphasized the importance of efficient AFIB detection when preventing stroke. In patients with existing brain scanning patients, subtle signs are often not diagnosed.

Technology development

Researchers trained AI models using other NVIDIA technologies such as NVIDIA A100 Tensorcore GPU and CUDA 12.1, Cudnn and NVIDIA APEX. Through this development, the model was able to handle a wide range of data sets with precision and facilitated AFIB’s identification in a cost -effective and less invasive manner compared to traditional ECG and heart monitoring methods.

The meaning of the future

The results are promising, but the team aims to verify the results with a larger sample and find external verification for a wider application. In successful, this AI -centered approach can transform a stroke strategy to make competitive MRI analysis a feasible alternative for early AFIB detection.

For more information, you can read the entire research on the NVIDIA blog.

Image Source: Shutter Stock


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