On-Line Graphics Recognition: State-of-the-Art

A brief survey on on-line graphics recognition is presented. We first present some common scenarios and applications of on-line graphics recognition and then identify major problems and sub-problems at three levels: primitive shape recognition, composite graphic object recognition, and document recognition and understanding. Representative approaches to these problems are also presented. We also list several open problems at the end

Multiple Myeloma DREAM Challenge reveals epigenetic regulator <em>PHF19</em> as marker of aggressive disease.

While the past decade has seen meaningful improvements in clinical outcomes for multiple myeloma patients, a subset of patients does not benefit from current therapeutics for unclear reasons. Many gene expression-based models of risk have been developed, but each model uses a different combination of genes and often involves assaying many genes making them difficult to implement. We organized the Multiple Myeloma DREAM Challenge, a crowdsourced effort to develop models of rapid progression in newly diagnosed myeloma patients and to benchmark these against previously published models. This effort lead to more robust predictors and found that incorporating specific demographic and clinical features improved gene expression-based models of high risk. Furthermore, post-challenge analysis identified a novel expression-based risk marker, PHF19, which has recently been found to have an important biological role in multiple myeloma. Lastly, we show that a simple four feature predictor composed of age, ISS, and expression of PHF19 and MMSET performs similarly to more complex models with many more gene expression features included