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Predicting the risk of mortality for patients with acute myocardial infarction (AMI) using electronic health records (EHRs) data can help identify risky patients who might need more tailored care. In our previous work, we built…

Machine Learning · Computer Science 2019-04-30 Seyedeh Neelufar Payrovnaziri , Laura A. Barrett , Daniel Bis , Jiang Bian , Zhe He

Respiratory illnesses are a significant global health burden. Respiratory illnesses, primarily Chronic obstructive pulmonary disease (COPD), is the seventh leading cause of poor health worldwide and the third leading cause of death…

Machine Learning · Computer Science 2024-10-31 Ankita Kumari Jain , Nitish Sharma , Madhav Kanda , Nipun Batra

Event-Based Models (EBMs) infer biomarker progression from cross-sectional data but typically only as ordinal sequences and rely on rigid model assumptions. We propose \textsc{Tempo}, a Transformer architecture that learns both ordinal and…

Machine Learning · Computer Science 2026-04-28 Hongtao Hao , Joseph L. Austerweil

While analysing time-to-event data, it is possible that a certain fraction of subjects will never experience the event of interest and they are said to be cured. When this feature of survival models is taken into account, the models are…

Methodology · Statistics 2020-01-27 Khandoker Akib Mohammad , Yuichi Hirose , Budhi Surya , Yuan Yao

Electronic health record (EHR) data are becoming an increasingly common data source for understanding clinical risk of acute events. While their longitudinal nature presents opportunities to observe changing risk over time, these analyses…

Systemic risk measures quantify the potential risk to an individual financial constituent arising from the distress of entire financial system. As a generalization of two widely applied risk measures, Value-at-Risk and Expected Shortfall,…

Methodology · Statistics 2025-11-24 Qingzhao Zhong , Yanxi Hou

Accelerated failure time (AFT) models are used widely in medical research, though to a much lesser extent than proportional hazards models. In an AFT model, the effect of covariates act to accelerate or decelerate the time to event of…

Methodology · Statistics 2020-06-15 Michael J. Crowther , Patrick Royston , Mark Clements

An important task in survival analysis is choosing a structure for the relationship between covariates of interest and the time-to-event outcome. For example, the accelerated failure time (AFT) model structures each covariate effect as a…

Methodology · Statistics 2025-12-08 Harrison T. Reeder , Kyu Ha Lee , Sebastien Haneuse

Wearable devices enable the continuous monitoring of physical activity (PA) but generate complex functional data with poorly characterized errors. Most work on functional data views the data as smooth, latent curves obtained at discrete…

Methodology · Statistics 2024-04-17 Xiwei Chen , Yuanyuan Luan , Roger S. Zoh , Lan Xue , Sneha Jadhav , Carmen D. Tekwe

We use recurrent-events survival analysis techniques and methods to analyze the duration of Olympic records. The Kaplan-Meier estimator is used to perform preliminary tests and recurrent event survivor function estimators proposed by Wang &…

Applications · Statistics 2012-07-27 Elliott Hollifield , Victoria Trevino , Adam Zarn

This study addresses the challenge of predicting post-stroke rigidity by emphasizing feature interactions through graph-based explainable AI. Post-stroke rigidity, characterized by increased muscle tone and stiffness, significantly affects…

Dynamic event prediction, using joint modeling of survival time and longitudinal variables, is extremely useful in personalized medicine. However, the estimation of joint models including many longitudinal markers is still a computational…

Methodology · Statistics 2024-12-13 Reza Hashemi , Taban Baghfalaki , Viviane Philipps , Helene Jacqmin-Gadda

Interval-censoring frequently occurs in studies of chronic diseases where disease status is inferred from intermittently collected biomarkers. Although many methods have been developed to analyze such data, they typically assume perfect…

Methodology · Statistics 2026-05-26 Yuhao Deng , Donglin Zeng , Yuanjia Wang

In this paper, the panel count data analysis for recurrent events is considered. Such analysis is useful for studying tumor or infection recurrences in both clinical trial and observational studies. A bivariate Gaussian Cox process model is…

Applications · Statistics 2019-02-19 Ye Liang , Yang Li , Bin Zhang

Palliative medicine is an interdisciplinary specialty focusing on improving quality of life (QOL) for patients with serious illness and their families. Palliative care programs are available or under development at over 80% of large US…

The concept of Quality of Life (QoL) refers to a holistic measurement of an individual's well-being, incorporating psychological and social aspects. Pregnant women, especially those with obesity and stress, often experience lower QoL.…

Machine Learning · Computer Science 2024-02-28 Kianoosh Kazemi , Iina Ryhtä , Iman Azimi , Hannakaisa Niela-Vilen , Anna Axelin , Amir M. Rahmani , Pasi Liljeberg

Physical activity energy expenditure (PAEE) can be measured from breath-by-breath respiratory data, which can serve as a reference. Alternatively, PAEE can be predicted from the body movements, which can be measured and estimated with…

Machine Learning · Computer Science 2025-07-28 Shuhao Que , Remco Poelarends , Peter Veltink , Miriam Vollenbroek-Hutten , Ying Wang

The presence of protein aggregates in cells is a known feature of many human age-related diseases, such as Huntington's disease. Simulations using fixed parameter values in a model of the dynamic evolution of expanded polyglutamine (PolyQ)…

Physical activity plays a significant role in the well-being of individuals with Chronic obstructive Pulmonary Disease (COPD). Specifically, it has been directly associated with changes in hospitalization rates for these patients. However,…

This paper provides guidance for researchers with some mathematical background on the conduct of time-to-event analysis in observational studies based on intensity (hazard) models. Discussions of basic concepts like time axis, event…

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