Abstract
Male breast cancer (MBC) patients seem to have inferior survival compared to female (FBC) ones, which is not fully explained by usual prognostic factors. Recurrence analysis could show differences in relapse patterns and/or in patients' approaches that justify these outcomes. Retrospective analysis of MBC patients treated in a cancer center between 1990 and 2014, looking for relapse. For each patient, three matched FBC patients were selected by: diagnosis' year, age (within 5 years), stage and tumors' type (only luminal-like were considered). Differences between cohorts were assessed by chi(2) test and hierarchical clustering was performed to define subgroups according to relapse local. Survival curves were calculated by Kaplan-Meier and compared using log-rank test. Statistical significance was defined as p < 0.05. Groups were balanced according to age, histological grade, stage, expression of hormonal receptors and adjuvant treatments. Median time to recurrence was equivalent, p = 0.72, with the majority of patients presented with distant metastases, p = 0.69, with more lung involvement in male, p =0.003. Male patients were more often proposed to symptomatic treatment (21.1% vs. 4.4%, p = 0.02). Overall and from recurrence survivals were poorer for male, median: 5 years [95% confidence interval (CI): 4.1-5.9 years] and 1 year (95% CI: 0-2.1 years) vs. 10 years (95% CI: 7.8-12.2 years) and 2 years (95% CI: 1.6-2.4 years), p < 0.001 and p = 0.004, respectively, and this tendency remained in the five cluster subgroups, that identified five patterns of relapse, p = 0.003. MBC patients had the worst survival, even after controlling important factors, namely the local of relapse. Palliative systemic treatment had favorable impact in prognosis and its frequently avoidance in male could justify the outcomes differences.

Abstract
Photogrowth is a creativity support tool for the creation of nonphoto-realistic renderings of images. The authors discuss its evolution from a generative art application to an interactive evolutionary art tool and finally into a meta-level interactive art system in which users express their artistic intentions through the design of a fitness function. The authors explore the impact of these changes on the sense of authorship, highlighting the range of imagery that can be produced by the system.

Abstract
Purpose: Male Breast Cancer (MBC) remains a poor understood disease. Prognostic factors are not well established and specific prognostic subgroups are warranted. Patients/methods: Retrospectively revision of 111 cases treated in the same Cancer Center. Blinded-central pathological revision with immunohistochemical (IHQ) analysis for estrogen (ER), progesterone (PR) and androgen (AR) receptors, HER2, ki67 and p53 was done. Cox regression model was used for uni/multivariate survival analysis. Two classifications of Female Breast Cancer (FBC) subgroups (based in ER, PR, HER2, 2000 classification, and in ER, PR, HER2, ki67, 2013 classification) were used to achieve their prognostic value in MBC patients. Hierarchical clustering was performed to define subgroups based on the six-IHQ panel. Results: According to FBC classifications, the majority of tumors were luminal: A (89.2%; 60.0%) and B (7.2%; 35.8%). Triple negative phenotype was infrequent (2.7%; 3.2%) and HER2 enriched, non-luminal, was rare (<= 1% in both). In multivariate analysis the poor prognostic factors were: size >2 cm (HR: 1.8; 95% CI: 1.0-3.4years, p = 0.049), absence of ER (HR: 4.9; 95% CI: 1.7-14.3years, p = 0.004) and presence of distant metastasis (HR: 5.3; 95% CI: 2.2-3.1years, p < 0.001). FBC subtypes were independent prognostic factors (p = 0.009, p = 0.046), but when analyzed only luminal groups, prognosis did not differ regardless the classification used (p > 0.20). Clustering defined different subgroups, that have prognostic value in multivariate analysis (p = 0.005), with better survival in ER/PR+, AR-, HER2- and ki67/p53 low group (median: 11.5 years; 95% CI: 6.2-16.8 years) and worst in PR-group (median: 4.5 years; 95% CI: 1.6 -7.8 years). Conclusion: FBC subtypes do not give the same prognostic information in MBC even in luminal groups. Two subgroups with distinct prognosis were identified in a common six-IHQ panel. Future studies must achieve their real prognostic value in these patients.

Abstract

Abstract

Abstract
Missing data consists in the lack of information in a dataset and since it directly influences classification performance, neglecting it is not a valid option. Over the years, several studies presented alternative imputation strategies to deal with the three missing data mechanisms, Missing Completely At Random, Missing At Random and Missing Not At Random. However, there are no studies regarding the influence of all these three mechanisms on the latest high-performance Artificial Intelligence techniques, such as Deep Learning. The goal of this work is to perform a comparison study between state-of-the-art imputation techniques and a Stacked Denoising Autoencoders approach. To that end, the missing data mechanisms were synthetically generated in 6 different ways; 8 different imputation techniques were implemented; and finally, 33 complete datasets from different open source repositories were selected. The obtained results showed that Support Vector Machines imputation ensures the best classification performance while Multiple Imputation by Chained Equations performs better in terms of imputation quality. © Springer Nature Switzerland AG 2018.