Identifying patterns of main causes of death in the young EU population

Effect of marital status on death rates. Part 1: High accuracy exploration of the Farr-Bertillon effect

The Farr-Bertillon law says that for all age-groups the death rate of married people is lower than the death rate of people who are not married (i.e. single, widowed or divorced). Although this law has been known for over 150 years, it has never been established with great accuracy. This even let some authors argue that it was a statistical artefact. It is true that the data must be selected and analyzed with great care, especially for age groups of small size such as widowers under 25. The observations reported in this paper were selected and designed in the same way as experiments in physics…

健康社会决定因素与美国各县芬太尼过量死亡率的关联：基于XGBoost和SHAP分析识别沉默风险县和治疗荒漠

Social Determinants of Health and Fentanyl Overdose Mortality Across US Counties: An XGBoost and SHAP Analysis Identifying Silent Risk Counties and Treatment Deserts

本文利用XGBoost和SHAP分析，探讨健康社会决定因素对美国各县芬太尼过量死亡率的影响，识别高风险地区及治疗不足区域，提出优先干预策略。

可视化和预测次国家级生命表死亡人数：差距预测方法

Visualizing and forecasting subnational life-table death counts: Gap forecasting methods

该研究针对次国家级生命表死亡人数的性别和地区差距问题，提出预测框架，结合累积分布函数变换，利用日本数据评估预测准确性，有助于深入理解死亡率差异的驱动因素。

Regularised B-splines projected Gaussian Process priors to estimate time-trends of age-specific COVID-19 deaths related to vaccine roll-out

The COVID-19 pandemic has caused severe public health consequences in the United States. In this study, we use a hierarchical Bayesian model to estimate the age-specific COVID-19 attributable deaths over time in the United States. The model is specified by a novel non-parametric spatial approach, a low-rank Gaussian Process (GP) projected by regularised B-splines. We show that this projection defines a new GP with attractive smoothness and computational efficiency properties, derive its kernel function, and discuss the penalty terms induced by the projected GP. Simulation analyses and benchmar…

Preliminary study of mortality by cause and sociodemographic characteristics, municipality of San Francisco, Antioquia (Columbia), 2001-2010

Objective: Determining the structure of mortality from causes and sociodemographic characteristics, in the municipality of San Francisco, Antioquia, 2001-2010. Methodology: Quantitative descriptive study with retrospective longitudinal data obtained from secondary source of death events through databases in electronic media supplied by the DANE. A description of the sociodemographic variables was performed by groups of cause of death, the life table by sex and years of potential life lost (APVP) for each year group and cause of death was calculated. Results: External causes and assaults, homic…

Interpretable (not just posthoc-explainable) medical claims modeling for discharge placement to prevent avoidable all-cause readmissions or death

We developed an inherently interpretable multilevel Bayesian framework for representing variation in regression coefficients that mimics the piecewise linearity of ReLU-activated deep neural networks. We used the framework to formulate a survival model for using medical claims to predict hospital readmission and death that focuses on discharge placement, adjusting for confounding in estimating causal local average treatment effects. We trained the model on a 5% sample of Medicare beneficiaries from 2008 and 2011, based on their 2009--2011 inpatient episodes, and then tested the model on 2012 e…