But girls still suck at science, right?
The grand prize in this year’s Google Science Fair went to Brittany Wenger, 17, who wrote a “global neural network cloud service” app–basically, a cloud-based brain with spectacular pattern-recognition capabilities that “learns” as more data is provided–to help doctors diagnose breast cancer. Using data from fine needle asiprates–traditionally one of the least invasive but least precise diagnostic procedures–Wenger’s Cloud4Cancer correctly identifies 99 percent of malignant tumors.
I once did a science fair project on which mouthwash was most effective at killing germs over time. I found that Listerine was pretty much an atomic bomb for your mouth, and after that you might as use saline. I think. It was a while ago.
The custom neural network achieved predictive success of 97.4% with 99.1% sensitivity to malignancy — substantially better than the evaluated commercial products. Out of the commercial products, two experienced consistent success while the third experienced erratic success. The sensitive to malignancy for the custom network was 5% higher than the best commercial network’s sensitivity. This experiment demonstrates modern neural networks can handle outliers and work with unmodified datasets to identify patterns. In addition, when all data is used for training, the custom network achieves 100% success with only 4 inconclusive samples, proving the network is more effective with more samples. Additionally, 7.6 million trials were run using different training sample sizes to demonstrate the sensitivity and predictive success improves as the network receives more training samples.
English translation? In early testing, Wenger’s app beat out three commercial apps currently in use and appears to get even more accurate as sample sizes increase. Wenger says she thinks her app “might best hospital ready” and would “love to get different data from doctors.” So… doctors, you’re up.