JointLIME: An interpretation method for machine learning survival models with endogenous time-varying covariates in credit scoring.

In this work, we introduce JointLIME, a novel interpretation method for explaining black-box survival (BBS) models with endogenous time-varying covariates (TVCs). Existing interpretation methods, like SurvLIME, are limited to BBS models only with time-invariant covariates. To fill this gap, JointLIME leverages the Local Interpretable Model-agnostic Explanations (LIME) framework to apply the joint model to approximate the survival functions predicted by the BBS model in a local area around a new individual.

Effectiveness of a grid mattress on adults' sleep quality and health: A quasi-experimental intervention study.

Background And Aims: Despite that 93% of people indicate that a mattress plays a pivotal role in achieving high-quality sleep, there is a scarcity of research investigating the influence of mattresses on sleep quality, pain, and mood in nonclinical poor sleepers. The purpose was to examine the effectiveness of a pressure-releasing medium-firm grid mattress on sleep and health outcomes (e.g.

On sparse ensemble methods: An application to short-term predictions of the evolution of COVID-19.

Since the seminal paper by Bates and Granger in 1969, a vast number of ensemble methods that combine different base regressors to generate a unique one have been proposed in the literature. The so-obtained regressor method may have better accuracy than its components, but at the same time it may overfit, it may be distorted by base regressors with low accuracy, and it may be too complex to understand and explain. This paper proposes and studies a novel Mathematical Optimization model to build a sparse ensemble, which trades off the accuracy of the ensemble and the number of base regressors used.

Modeling Antimicrobial Prescriptions in Scotland: A Spatiotemporal Clustering Approach.

In 2016, the British government acknowledged the importance of reducing antimicrobial prescriptions to avoid the long-term harmful effects of overprescription. Prescription needs are highly dependent on the factors that have a spatiotemporal component, such as bacterial outbreaks and urban densities. In this context, density-based clustering algorithms are flexible tools to analyze data by searching for group structures and therefore identifying peer groups of GPs with similar behavior.

Effect of a Free-Living Ketogenic Diet on Feasibility, Satiety, Body Composition, and Metabolic Health in Women: The Grading Level of Optimal Carbohydrate for Women (GLOW) Study.

Objective: The study's purpose was to examine a free-living, ketogenic diet (WFKD) on feasibility, satiety, body composition, and metabolic health in women.

Methods: Twenty-two women (age (yr.) 42.