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AI Model Predicts Surgery Risks with 85% Accuracy

9/18/2025

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Summary

Story summary

Researchers at Johns Hopkins created an AI model that predicts post-surgery complications using routine electrocardiograms (ECGs).
The AI achieved 85% accuracy in identifying patients at risk of heart attacks, strokes, or death within 30 days post-surgery, surpassing traditional tools at 60% accuracy.
It analyzes ECG data alongside patient medical records for better predictions.
The findings could enhance surgical risk assessments and patient-surgeon discussions.
Future research will involve testing the model on more patients and exploring further insights from ECG data.

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Story summary

Researchers at Johns Hopkins created an AI model that predicts post-surgery complications using routine electrocardiograms (ECGs).
The AI achieved 85% accuracy in identifying patients at risk of heart attacks, strokes, or death within 30 days post-surgery, surpassing traditional tools at 60% accuracy.
It analyzes ECG data alongside patient medical records for better predictions.
The findings could enhance surgical risk assessments and patient-surgeon discussions.
Future research will involve testing the model on more patients and exploring further insights from ECG data.