Tootfinder

Viele Menschen verstehen #Warnungen wie „#Hitzeindex“ oder „#Hitzewarnung“ falsch. Das zeigt eine US-Studie.
Fast die Hälfte hält den Hitzeindex für die reine

Bridging the Gap between National Weather Service Heat Terminology and Public Understanding
Abstract Clearly communicating heat warning information to the public is an important way to reduce heat mortality and morbidity. However, heat communication interventions from the National Weather Service commonly include technical and scientific terms, otherwise known as jargon. These terms, such as heat advisory or heat index, may not be understood by the public. Given the importance of message understanding in protective action decision-making, the purpose of this study is to assess how the…

Analyzing Pension Fund Mortality with Gaussian Processes in a Sub Population Framework
Eduardo F. L. de Melo, Michael Ludkovski, Rodrigo S. Targino
https://arxiv.org/abs/2506.03584

Analyzing Pension Fund Mortality with Gaussian Processes in a Sub Population Framework
Pension fund populations often have mortality experiences that are substantially different from the national benchmark. In a motivating case study of Brazilian corporate pension funds, pensioners are observed to have mortality that is 40-55% below the national average, due to the underlying socioeconomic disparities. Direct analysis of a pension fund population is challenging due to very sparse data, with age-specific annual death counts often in low single digits. We design and study a collect…

This https://arxiv.org/abs/2506.00095 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

ClinBench-HPB: A Clinical Benchmark for Evaluating LLMs in Hepato-Pancreato-Biliary Diseases
Hepato-pancreato-biliary (HPB) disorders represent a global public health challenge due to their high morbidity and mortality. Although large language models (LLMs) have shown promising performance in general medical question-answering tasks, the current evaluation benchmarks are mostly derived from standardized examinations or manually designed questions, lacking HPB coverage and clinical cases. To address these issues, we systematically eatablish an HPB disease evaluation benchmark comprising…

Predicting Postoperative Stroke in Elderly SICU Patients: An Interpretable Machine Learning Model Using MIMIC Data
Tinghuan Li, Shuheng Chen, Junyi Fan, Elham Pishgar, Kamiar Alaei, Greg Placencia, Maryam Pishgar
https://arxiv.org/abs/2506.03209

Predicting Postoperative Stroke in Elderly SICU Patients: An Interpretable Machine Learning Model Using MIMIC Data
Postoperative stroke remains a critical complication in elderly surgical intensive care unit (SICU) patients, contributing to prolonged hospitalization, elevated healthcare costs, and increased mortality. Accurate early risk stratification is essential to enable timely intervention and improve clinical outcomes. We constructed a combined cohort of 19,085 elderly SICU admissions from the MIMIC-III and MIMIC-IV databases and developed an interpretable machine learning (ML) framework to predict in…

Joint Modeling for Learning Decision-Making Dynamics in Behavioral Experiments
Yuan Bian, Xingche Guo, Yuanjia Wang
https://arxiv.org/abs/2506.02394 https:…

Joint Modeling for Learning Decision-Making Dynamics in Behavioral Experiments
Major depressive disorder (MDD), a leading cause of disability and mortality, is associated with reward-processing abnormalities and concentration issues. Motivated by the probabilistic reward task from the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study, we propose a novel framework that integrates the reinforcement learning (RL) model and drift-diffusion model (DDM) to jointly analyze reward-based decision-making with response times. To acc…

Dear men.
Please stop shaming our gender by being this kind of idiot.
Thank you.
https://beige.party/@RickiTarr/114597143638854656

Beyond water limitation in vegetation-autotoxicity patterning: a cross-diffusion model
Francesco Giannino, Annalisa Iuorio, Cinzia Soresina
https://arxiv.org/abs/2506.03981

Beyond water limitation in vegetation-autotoxicity patterning: a cross-diffusion model
Many mathematical models describing vegetation patterns are based on biomass--water interactions, due to the impact of this limited resource in arid and semi-arid environments. However, in recent years, a novel biological factor called autotoxicity has proved to play a key role in vegetation spatiotemporal dynamics, particularly by inhibiting biomass growth and increasing its natural mortality rate. In a standard reaction-diffusion framework, biomass-toxicity dynamics alone are unable to suppor…

Long-term impact of PM2.5 on mortality is exacerbated when wildfire events occur
Federica Spoto, Francesca Dominici, Danielle Braun, Joan A. Casey
https://arxiv.org/abs/2505.16613

Long-term impact of PM2.5 on mortality is exacerbated when wildfire events occur
There is extensive evidence that long-term exposure to all-source PM2.5 increases mortality. However, to date, no study has evaluated whether this effect is exacerbated in the presence of wildfire events. Here, we study 60+ million older US adults and find that wildfire events increase the harmful effects of long-term all-source PM2.5 exposure on mortality, providing a new and realistic conceptualization of wildfire health risks.

This https://arxiv.org/abs/2506.00095 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

ClinBench-HPB: A Clinical Benchmark for Evaluating LLMs in Hepato-Pancreato-Biliary Diseases
Hepato-pancreato-biliary (HPB) disorders represent a global public health challenge due to their high morbidity and mortality. Although large language models (LLMs) have shown promising performance in general medical question-answering tasks, the current evaluation benchmarks are mostly derived from standardized examinations or manually designed questions, lacking HPB coverage and clinical cases. To address these issues, we systematically eatablish an HPB disease evaluation benchmark comprising…

ClinBench-HPB: A Clinical Benchmark for Evaluating LLMs in Hepato-Pancreato-Biliary Diseases
Yuchong Li, Xiaojun Zeng, Chihua Fang, Jian Yang, Lei Zhang
https://arxiv.org/abs/2506.00095

ClinBench-HPB: A Clinical Benchmark for Evaluating LLMs in Hepato-Pancreato-Biliary Diseases
Hepato-pancreato-biliary (HPB) disorders represent a global public health challenge due to their high morbidity and mortality. Although large language models (LLMs) have shown promising performance in general medical question-answering tasks, the current evaluation benchmarks are mostly derived from standardized examinations or manually designed questions, lacking HPB coverage and clinical cases. To address these issues, we systematically eatablish an HPB disease evaluation benchmark comprising…

This https://arxiv.org/abs/2505.12485 has been replaced.
initial toot: https://mastoxiv.page/@arX…

A Reduced-Order CFD Approach for Intermediate grade Coronary Arterial Clinical Parameter Assessment A Reduced-Order CFD Approach for Intermediate grade Coronary Arterial Clinical Parameter Assessment
Coronary heart disease (CHD) remains a top reason of mortality worldwide. This study introduces a novel approach by integrating patient-specific Multi-slice CT scans into CAD models and employing a one-dimensional numerical framework to assess varying degrees of stenosis. The computational analysis encompasses the entire arterial tree, with a particular focus on stenosed coronary arteries modelled using an analytical equation. One-dimensional characteristic equations, utilizing forward and back…

This https://arxiv.org/abs/2505.13185 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qfi…

Filtering in a hazard rate change-point model with financial and life-insurance applications
This paper develops a continuous-time filtering framework for estimating a hazard rate subject to an unobservable change-point. This framework arises naturally in both financial and insurance applications, where the default intensity of a firm or the mortality rate of an individual may experience a sudden jump at an unobservable time, representing, for instance, a shift in the firm's risk profile or a deterioration in an individual's health status. By employing a progressive enlargement of filt…

Filtering in a hazard rate change-point model with financial and life-insurance applications
Matteo Buttarazzi, Claudia Ceci
https://arxiv.org/abs/2505.13185

Filtering in a hazard rate change-point model with financial and life-insurance applications
This paper develops a continuous-time filtering framework for estimating a hazard rate subject to an unobservable change-point. This framework arises naturally in both financial and insurance applications, where the default intensity of a firm or the mortality rate of an individual may experience a sudden jump at an unobservable time, representing, for instance, a shift in the firm's risk profile or a deterioration in an individual's health status. By employing a progressive enlargement of filt…