1623
clinical study

The utility of deep learning: evaluation of a convolutional neural network for detection of intracranial bleeds on non-contrast head computed tomography studies

Accuracy, Intracranial Hemorrhage

Materials & Methods

The algorithm was tested on 7,112 non-contrast head CTs acquired during 2016–2017 from two, large urban academic and trauma centers. 

Results

Promising results of a scalable and clinically pragmatic AI model tested on a large set of real-world data from high-volume medical centers. Results showed a 98% level of accuracy, with 95% sensitivity and over 98% specificity. 

Conclusions

The AI algorithm had high levels of accuracy (98%), sensitivity (95%) and over 98% specificity (98%)

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