QuMinS: fast and scalable querying, mining and summarizing multi-modal databases

Given a large image set, in which very few images have labels, how to guess labels for the remaining majority? How to spot images that need brand new labels different from the predefined ones? How to summarize these data to route the user’s attention to what really matters? Here we answer all these questions. Specifically, we propose QuMinS, a fast, scalable solution to two problems: (i) Low-labor labeling (LLL) – given an image set, very few images have labels, find the most appropriate labels for the rest; and (ii) Mining and attention routing – in the same setting, find clusters, the top-'N IND.O' outlier images, and the 'N IND.R' images that best represent the data. Experiments on satellite images spanning up to 2.25 GB show that, contrasting to the state-of-the-art labeling techniques, QuMinS scales linearly on the data size, being up to 40 times faster than top competitors (GCap), still achieving better or equal accuracy, it spots images that potentially require unpredicted labels, and it works even with tiny initial label sets, i.e., nearly five examples. We also report a case study of our method’s practical usage to show that QuMinS is a viable tool for automatic coffee crop detection from remote sensing images.

ESMO Consensus Guidelines for management of patients with colon and rectal cancer. A personalized approach to clinical decision making

Colorectal cancer (CRC) is the most common tumour type in both sexes combined in Western countries. Although screening programmes including the implementation of faecal occult blood test and colonoscopy might be able to reduce mortality by removing precursor lesions and by making diagnosis at an earlier stage, the burden of disease and mortality is still high. Improvement of diagnostic and treatment options increased staging accuracy, functional outcome for early stages as well as survival. Although high quality surgery is still the mainstay of curative treatment, the management of CRC must be a multi-modal approach performed by an experienced multi-disciplinary expert team. Optimal choice of the individual treatment modality according to disease localization and extent, tumour biology and patient factors is able to maintain quality of life, enables long-term survival and even cure in selected patients by a combination of chemotherapy and surgery. Treatment decisions must be based on the available evidence, which has been the basis for this consensus conference-based guideline delivering a clear proposal for diagnostic and treatment measures in each stage of rectal and colon cancer and the individual clinical situations. This ESMO guideline is recommended to be used as the basis for treatment and management decisions.