相关论文: A semiparametric regression model for paired longi…
Blood Pressure (BP) and Heart Rate (HR) provide information on clin-ical condition along 24h. Both signals present circadian changes due to sympa-thetic/parasympathetic control system that influence the relationship between them. Moreover,…
Cardiovascular disease (CVD) cohort studies collect longitudinal data on numerous CVD risk factors including body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), glucose, and total cholesterol. The commonly…
We investigate the parameter estimation of regression models with fixed group effects, when the group variable is missing while group related variables are available. This problem involves clustering to infer the missing group variable…
The Cox proportional hazards model is routinely used to analyze time-to-event data. To use this model requires the definition of a unique well-defined time scale. Most often, observation time is used as the time scale for both clinical and…
Quantitative evidence synthesis methods aim to combine data from multiple medical trials to infer relative effects of different interventions. A challenge arises when trials report continuous outcomes on different measurement scales. To…
Hypertension is a global health concern with an increasing prevalence, underscoring the need for effective monitoring and analysis of blood pressure (BP) dynamics. We analyzed a substantial BP dataset comprising 75,636,128 records from…
In the present study we investigate overall population effects on episodic memory of an intervention over 15 years that reduces systolic blood pressure in individuals with hypertension. A limitation with previous research on the potential…
In this work, blood pressure eleven years ahead is modeled using data from a longitudinal population-based health survey, the Trondelag Health (HUNT) Study, while accounting for missing data due to dropout between consecutive surveys (20-50…
High blood pressure (hypertension) is the number one risk factor for premature death. Hypertension is asymptomatic, so blood pressure must be regularly monitored to diagnose it. In auscultatory blood pressure measurement, a patient's…
Purpose: To show some preliminary results about the possibility to exploit a cardiovascular mathematical model - made patient-specific by noninvasive data routinely measured during ordinary clinical examinations - in order to obtain…
Statistical shape modeling (SSM) is a valuable and powerful tool to generate a detailed representation of complex anatomy that enables quantitative analysis and the comparison of shapes and their variations. SSM applies mathematics,…
Modeling of growth (or decay) curves arises in many fields such as microbiology, epidemiology, marketing, and econometrics. Parametric forms like Logistic and Gompertz are often used for modeling such monotonic patterns. While useful for…
The identification of factors associated with mental and behavioral disorders in early childhood is critical both for psychopathology research and the support of primary health care practices. Motivated by the Millennium Cohort Study, in…
Joint modeling of longitudinal and survival data has become increasingly important in medical research, particularly for understanding disease progression in chronic conditions where both repeated biomarker measurements and time-to-event…
Many applications involve data with qualitative and quantitative responses. When there is an association between the two responses, a joint model will provide improved results than modeling them separately. In this paper, we propose a…
In clinical trials where long follow-up is required to measure the primary outcome of interest, there is substantial interest in using an accepted surrogate outcome that can be measured earlier in time or with less cost to estimate a…
The systematic collection of longitudinal data is very common in practice, making mixed models widely used. Most developments around these models focus on modeling the mean trajectory of repeated measurements, typically under the assumption…
It is often of interest to combine available estimates of a similar quantity from multiple data sources. When the corresponding variances of each estimate are also available, a model should take into account the uncertainty of the estimates…
The use of observed wearable sensor data (e.g., photoplethysmograms [PPG]) to infer health measures (e.g., glucose level or blood pressure) is a very active area of research. Such technology can have a significant impact on health…
We have performed surface tension measurements on carbopol gels of different concentrations and yield stresses. Our setup, based on the force exerted by a capillary bridge on two parallel plates, allows to measure an effective surface…