US Department of Energy Unveils Post-Exascale R&D Program

At the conclusion of 2021, researchers at UNC Charlotte and Duke University Medical Center published results of work done to use transfer learning methods to generate fluence maps for radiation therapy, aimed at providing medical professionals with more capability and information in fighting adrenal cancers. The technique uses a deep transfer learning model trained on a much larger dataset that can be applied to a smaller data set for a specific application.

• The initial model was trained on pancreas treatment plans, then retuned and applied to a smaller set of data points on adrenal cancers. The output of the model generates a fluence map for specific IMRT beam-based treatments for adrenal cancers.
• According to the researchers, this approach is meant to supplement but not replace human expertise in the field and is reliant on human expertise to finetune and improve the AI model.

During the recent conference held by the Special Interest Group on Knowledge Discovery and Data Mining held in Singapore, three international public science policy advocacy groups presented a guide, Using Artificial Intelligence to Support Healthcare Decisions, aimed at empowering and educating the public on the growing use of AI platforms in the healthcare decision-making process. The guide covers explanations of common applications of artificial intelligence platforms in healthcare and, more importantly, outlines specific questions one can pose to cut to the core of the efficacy and reliability of an AI platform in those applications.