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Using artificial intelligence in a primary care setting to identify patients at risk for cancer

Started ‎02-10-2023 by
Modified ‎02-10-2023 by
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Published in Clinical Medicine and Laboratory Medicine, 60(12), pp. 2005-2016.

Objectives:

To evaluate the ability of an artificial intelligence (AI) model to predict the risk of cancer in patients referred from primary care based on routine blood tests. Results obtained with the AI model are compared to results based on logistic regression (LR).

Results:

The AI model based on routine laboratory blood tests can provide an easy-to use risk score to predict cancer within 90 days. Results obtained with the AI model were comparable to results from the LR model. In the internal validation Cohort IB, the AI model provided slightly better results than the LR analysis both in terms of the area under the receiver operating characteristics curve (AUC) and PPV, sensitivity/specificity while in the “out of time” validation test Cohort II, the obtained results were comparable.

 

 

Soerensen, P.D., Christensen, H.,  Worsoe Laursen, S. G., Hardahl, C.,  Brandslund, I, and Skov Madsen, J. (2021), Clinical Medicine and Laboratory Medicine (CCLM), 60(12), pp. 2005-2016.

Using artificial intelligence in a primary care setting to identify patients at risk for cancer: a r...

 

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