IBM Watson Uses AI to Determine Patients Who Need Contrast

The aim was to develop and validate a machine learning-based natural language classifier capable of automatically assigning the use of intravenous contrast for musculoskeletal MRI protocols, based upon the study’s free-text clinical indication, thus improving efficiency of the protocoling radiologist and potentially reducing errors.

The researchers then compared the accuracy of IBM Watson, traditional computers, and a radiologist for determining which patients should receive contrast for musculoskeletal MRI scans based upon clinical indications. They found that Watson achieved an overall accuracy of 83.2% as compared to the original radiologist. In addition to its high accuracy in assigning MRI contrast, IBM Watson also offers the advantage of functioning without preprocessing, with the operator requiring only a minimal understanding of machine-learning fundamentals, according to the researchers.

The researchers concluded that the implementation of this automated MRI contrast determination system as a clinical decision support tool can save significant time and effort for the radiologist while potentially reducing error rates, and does not require any change in order entry or workflow.