Solving k-center Clustering (with Outliers) in MapReduce and Streaming, almost as Accurately as Sequentially.

Center-based clustering is a fundamental primitive for data analysis and becomes very challenging for large datasets. In this paper, we focus on the popular k-center variant which, given a set S of points from some metric space and a parameter k0, the algorithms yield solutions whose approximation ratios are a mere additive term \u3f5 away from those achievable by the best known polynomial-time sequential algorithms, a result that substantially improves upon the state of the art. Our algorithms are rather simple and adapt to the intrinsic complexity of the dataset, captured by the doubling dimension D of the metric space. Specifically, our analysis shows that the algorithms become very space-efficient for the important case of small (constant) D. These theoretical results are complemented with a set of experiments on real-world and synthetic datasets of up to over a billion points, which show that our algorithms yield better quality solutions over the state of the art while featuring excellent scalability, and that they also lend themselves to sequential implementations much faster than existing ones

A toolbox for a structured risk-based prehabilitation program in major surgical oncology

Prehabilitation is a multimodal concept to improve functional capability prior to surgery, so that the patients’ resilience is strengthened to withstand any peri- and postoperative comorbidity. It covers physical activities, nutrition, and psychosocial wellbeing. The literature is heterogeneous in outcomes and definitions. In this scoping review, class 1 and 2 evidence was included to identify seven main aspects of prehabilitation for the treatment pathway: (i) risk assessment, (ii) FITT (frequency, interventions, time, type of exercise) principles of prehabilitation exercise, (iii) outcome measures, (iv) nutrition, (v) patient blood management, (vi) mental wellbeing, and (vii) economic potential. Recommendations include the risk of tumor progression due to delay of surgery. Patients undergoing prehabilitation should perceive risk assessment by structured, quantifiable, and validated tools like Risk Analysis Index, Charlson Comorbidity Index (CCI), American Society of Anesthesiology Score, or Eastern Co-operative Oncology Group scoring. Assessments should be repeated to quantify its effects. The most common types of exercise include breathing exercises and moderate- to high-intensity interval protocols. The program should have a duration of 3–6 weeks with 3–4 exercises per week that take 30–60 min. The 6-Minute Walking Testing is a valid and resource-saving tool to assess changes in aerobic capacity. Long-term assessment should include standardized outcome measurements (overall survival, 90-day survival, Dindo–Clavien/CCI®) to monitor the potential of up to 50% less morbidity. Finally, individual cost-revenue assessment can help assess health economics, confirming the hypothetic saving of $8 for treatment for$1 spent for prehabilitation. These recommendations should serve as a toolbox to generate hypotheses, discussion, and systematic approaches to develop clinical prehabilitation standards