AI to predict thyroid cancer risk in ultrasound

New York: Using Artificial Intelligence (AI) with thyroid ultrasound offers a quick and non-invasive approach to thyroid cancer screening, says a new study.
The study, published in the journal PLOS Pathogens, suggests that automated machine learning shows promise as an additional diagnostic tool that could improve the efficiency of thyroid cancer diagnosis.
“Machine learning is a low-cost and efficient tool that could help physicians arrive at a quicker decision as to how to approach an indeterminate nodule,” said the study’s lead author John Eisenbrey from Thomas Jefferson University in the US.
According to the researchers, at present ultrasounds can tell if a nodule looks suspicious, and then the decision is made whether to do a needle biopsy, but fine-needle biopsies only act as a peephole, they don’t reveal the whole picture.
As a result, some biopsies return inconclusive results as to whether the nodule is malignant, or cancerous in other words.
In order to improve the predictive power of the first-line diagnostic, the ultrasound, researchers looked into machine learning or AI models developed by Google.