Sudden chest pain poses a critical diagnostic challenge, necessitating swift differentiation between heart attacks and aortic dissections. Both are life-threatening, characterized by overlapping symptoms like chest pain and shortness of breath, but require different treatments. Researchers from the People’s Hospital of Xinjiang and Xinjiang University have developed an innovative AI-powered diagnostic method that analyzes blood samples for rapid identification of these conditions. Using just a drop of blood, this method offers results within 10 minutes, boasting a clinical accuracy of 94.06% and specificity of 97.03%. By combining infrared and Raman spectroscopy with a deep learning model, the approach reveals distinct biochemical “fingerprints,” enabling precise diagnostics. This low-cost solution can be utilized in emergency settings, providing a crucial alternative to contrast-enhanced CT scans. The team plans to further develop this technology into a portable device, streamlining diagnosis and treatment in real-world medical scenarios.
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