WAW-TACE: A Hepatocellular Carcinoma Multiphase CT Dataset with Segmentations, Radiomics Features, and Clinical Data.

The WAW-TACE dataset contains baseline multiphase abdominal CT images from 233 treatment-naive patients with hepatocellular carcinoma treated with transarterial chemoembolization and includes 377 handcrafted liver tumor masks, automated segmentations of multiple internal organs, extracted radiomics features, and corresponding extensive clinical data. The dataset can be accessed at .

A novel radiomics approach for predicting TACE outcomes in hepatocellular carcinoma patients using deep learning for multi-organ segmentation.

Transarterial chemoembolization (TACE) represent the standard of therapy for non-operative hepatocellular carcinoma (HCC), while prediction of long term treatment outcomes is a complex and multifactorial task. In this study, we present a novel machine learning approach utilizing radiomics features from multiple organ volumes of interest (VOIs) to predict TACE outcomes for 252 HCC patients. Unlike conventional radiomics models requiring laborious manual segmentation limited to tumoral regions, our approach captures information comprehensively across various VOIs using a fully automated, pretrained deep learning model applied to pre-TACE CT images.

Continuous, self-sustaining smouldering destruction of simulated faeces.

A new approach for the rapid destruction of human waste using smouldering combustion is presented. Recently, self-sustaining smouldering combustion was shown to destroy the organic component of simulated human solid waste and dog faeces resulting in the sanitization of all pathogens using a batch process (Yermán et al., 2015).

An incremental design of radial basis function networks.

This paper proposes an offline algorithm for incrementally constructing and training radial basis function (RBF) networks. In each iteration of the error correction (ErrCor) algorithm, one RBF unit is added to fit and then eliminate the highest peak (or lowest valley) in the error surface. This process is repeated until a desired error level is reached.

Bond-valence parameters of lanthanides.

Ln-O and Ln-N bond-valence parameters have been computed in coordination complexes for lanthanides (Ln) at oxidation states other than +3 (Ce(IV), Sm(II), Eu(II) and Yb(II)). Moreover, Ln-Cl, Ln-S and Ln-C(pi-bonded) bond-valence parameters are presented, as calculated for coordination compounds. In general, the bond-valence parameters decrease in the order Ln-O > Ln-C > Ln-N > Ln-Cl > Ln-S.