Ensuring AI Accuracy in Cancer Care

Anil Parwani, MD, PhD, professor of pathology at The Ohio State University Wexner Medical Center, addresses potential biases or limitations in the artificial intelligence (AI) algorithm used at his institution, particularly concerning factors like patient demographics or socioeconomic status, and what their goals for the future entail.

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0:09 | We absolutely want to be very careful with this. In our hospital, our demographics, we know what type of population of patients we serve, depending on the greater Columbus area or central Ohio region. But what if the AI algorithm was designed for patients in Sweden, or patients in China, or patients in Japan? So, is it directly applicable? Can we find the same answers that those algorithms are designed for? So generally speaking, these algorithms have extensive validation done before they are ready to be used. But we at Ohio State are even more cautious, we do our own internal validation. We take a known patient with a known cancer, a known grade, and we use that to train the algorithm and test the algorithm over and over again.

1:12 | We have published this data recently, where we have demonstrated that the pathologist’s diagnosis and the AI diagnosis are not different from each other, they are not inferior to each other. We do this very carefully because once we lock down the algorithm, that is, we have used it and locked it down, then it becomes a routine algorithm for cancer care. That is why in the next few months, our goal is to take the commercially available algorithms, they were probably designed on patients from different parts of the world, and to bring it to Ohio, test it here on our patients, and then release it for effective use for prostate cancer detection.

2:04 | We are also doing the same thing for breast cancer, and gastric cancer. We are also doing it for non cancers, like detecting microorganisms in a gastric biopsy like H. Pylori. It is really an exciting time. When I went to medical school, I didn't even know this would be a possibility in the future. But today, I am very excited and I am very pleased that we have these tools now for patient care and for oncology care.