Multitasking AI enables fastest cancer data retrieval yet

Written by Celeste Brady, Commissioning Editor

A new, multi-task convolutional neural network is able to extract data from cancer pathology reports multiple times faster than the single-task, deep-learning models or manual data extraction currently in use. Researchers at Oak Ridge National Laboratory (TN, USA) have developed a multi-task learning convolutional neural network to extract data from cancer pathology reports — an artificial intelligence tool capable of extracting multiple characteristics from the complex and extensive information included in pathology reports. The project could benefit research which utilizes digital cancer registries to find trends in cancer diagnoses and patients’ responses to treatment. This is helpful to policy and...

To view this content, please register now for access

It's completely free