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A new AI-based software has been developed that is reported to be twice as accurate as traditional visual methods in determining the time a stroke occurred. This advancement could significantly enhance emergency medical decisions, allowing for better treatment options for stroke patients. Researchers believe that utilizing this technology could lead to up to 50% more patients receiving appropriate care.
The software, created by a collaboration of researchers from Imperial College London, Technical University of Munich, and Edinburgh University, was trained on 800 brain scans and tested on 2,000 patients. The findings suggest that the AI model's ability to analyze additional features from scans, such as texture, contributes to its superior accuracy. This innovation not only aids in timely treatment but also has the potential for full automation in clinical settings.
• AI software improves stroke time detection accuracy significantly.
• Up to 50% more stroke patients could receive appropriate treatment.
Artificial intelligence refers to computer systems that simulate human intelligence, enhancing medical decision-making.
An algorithm is a set of rules or calculations used by the AI to analyze brain scans for stroke detection.
Imperial College London is involved in AI research, particularly in developing software for medical applications.
Technical University of Munich contributes to AI advancements in healthcare, focusing on stroke detection technologies.
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