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Total 793 results found since Jan 2013.

A Review on the Extraction of Quantitative Retinal Microvascular Image Feature.
Authors: Kipli K, Hoque ME, Lim LT, Mahmood MH, Sahari SK, Sapawi R, Rajaee N, Joseph A Abstract Digital image processing is one of the most widely used computer vision technologies in biomedical engineering. In the present modern ophthalmological practice, biomarkers analysis through digital fundus image processing analysis greatly contributes to vision science. This further facilitates developments in medical imaging, enabling this robust technology to attain extensive scopes in biomedical engineering platform. Various diagnostic techniques are used to analyze retinal microvasculature image to enable geometric fe...
Source: Computational and Mathematical Methods in Medicine - August 3, 2018 Category: Statistics Tags: Comput Math Methods Med Source Type: research

A Poincare Map Based Analysis of Stroke Patients' Walking after a Rehabilitation by a Robot.
Abstract Since the past decade, rehabilitation robots have become common technologies for recovering gait ability after a stroke. Nevertheless, it is believed that these robots can be further enhanced. Hence, several researches are making progress in optimizing gait rehabilitation robots. However, most of these researches have only assessed the robots and their controllers in improving spatiotemporal and kinetic features of walking. There are not many researchers have focused on the robots' controllers' effects on the central nervous or neuromuscular systems. On the other hand, recently computational methods have ...
Source: Mathematical Biosciences - March 5, 2018 Category: Statistics Authors: Abedi M, Moghaddam MM, Fallah D Tags: Math Biosci Source Type: research

Improved precision in the analysis of randomized trials with survival outcomes, without assuming proportional hazards
We present a new estimator of the restricted mean survival time in randomized trials where there is right censoring that may depend on treatment and baseline variables. The proposed estimator leverages prognostic baseline variables to obtain equal or better asymptotic precision compared to traditional estimators. Under regularity conditions and random censoring within strata of treatment and baseline variables, the proposed estimator has the following features: (i) it is interpretable under violations of the proportional hazards assumption; (ii) it is consistent and at least as precise as the Kaplan –Meier and inverse pr...
Source: Lifetime Data Analysis - February 28, 2018 Category: Statistics Source Type: research

Sensitivity analysis for unobserved confounding of direct and indirect effects using uncertainty intervals
To estimate direct and indirect effects of an exposure on an outcome from observed data, strong assumptions about unconfoundedness are required. Since these assumptions cannot be tested using the observed data, a mediation analysis should always be accompanied by a sensitivity analysis of the resulting estimates. In this article, we propose a sensitivity analysis method for parametric estimation of direct and indirect effects when the exposure, mediator, and outcome are all binary. The sensitivity parameters consist of the correlations between the error terms of the exposure, mediator, and outcome models. These correlation...
Source: Statistics in Medicine - February 21, 2018 Category: Statistics Authors: Anita Lindmark, Xavier Luna, Marie Eriksson Tags: RESEARCH ARTICLE Source Type: research

Investigation of 2 ‐stage meta‐analysis methods for joint longitudinal and time‐to‐event data through simulation and real data application
ConclusionsWhere evidence of association between longitudinal and time‐to‐event outcomes exists, results from joint models over standalone analyses should be pooled in 2‐stage meta‐analyses.
Source: Statistics in Medicine - December 18, 2017 Category: Statistics Authors: Maria Sudell, Catrin Tudur Smith, Fran çois Gueyffier, Ruwanthi Kolamunnage‐Dona Tags: RESEARCH ARTICLE Source Type: research

A clinical trial design using the concept of proportional time using the generalized gamma ratio distribution
Traditional methods of sample size and power calculations in clinical trials with a time‐to‐event end point are based on the logrank test (and its variations), Cox proportional hazards (PH) assumption, or comparison of means of 2 exponential distributions. Of these, sample size calculation based on PH assumption is likely the most common and allows adjusting for the effect of one or more covariates. However, when designing a trial, there are situations when the assumption of PH may not be appropriate. Additionally, when it is known that there is a rapid decline in the survival curve for a control group, such as from pr...
Source: Statistics in Medicine - August 16, 2017 Category: Statistics Authors: Milind A. Phadnis, James B. Wetmore, Matthew S. Mayo Tags: RESEARCH ARTICLE Source Type: research

Perfusion Angiography in Acute Ischemic Stroke.
Authors: Scalzo F, Liebeskind DS Abstract Visualization and quantification of blood flow are essential for the diagnosis and treatment evaluation of cerebrovascular diseases. For rapid imaging of the cerebrovasculature, digital subtraction angiography (DSA) remains the gold standard as it offers high spatial resolution. This paper lays out a methodological framework, named perfusion angiography, for the quantitative analysis and visualization of blood flow parameters from DSA images. The parameters, including cerebral blood flow (CBF) and cerebral blood volume (CBV), mean transit time (MTT), time-to-peak (TTP), and...
Source: Computational and Mathematical Methods in Medicine - July 26, 2016 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Abnormal EEG Complexity and Functional Connectivity of Brain in Patients with Acute Thalamic Ischemic Stroke.
Authors: Liu S, Guo J, Meng J, Wang Z, Yao Y, Yang J, Qi H, Ming D Abstract Ischemic thalamus stroke has become a serious cardiovascular and cerebral disease in recent years. To date the existing researches mostly concentrated on the power spectral density (PSD) in several frequency bands. In this paper, we investigated the nonlinear features of EEG and brain functional connectivity in patients with acute thalamic ischemic stroke and healthy subjects. Electroencephalography (EEG) in resting condition with eyes closed was recorded for 12 stroke patients and 11 healthy subjects as control group. Lempel-Ziv complexity...
Source: Computational and Mathematical Methods in Medicine - July 14, 2016 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Calibrating random forests for probability estimation
Probabilities can be consistently estimated using random forests. It is, however, unclear how random forests should be updated to make predictions for other centers or at different time points. In this work, we present two approaches for updating random forests for probability estimation. The first method has been proposed by Elkan and may be used for updating any machine learning approach yielding consistent probabilities, so‐called probability machines. The second approach is a new strategy specifically developed for random forests. Using the terminal nodes, which represent conditional probabilities, the random forest ...
Source: Statistics in Medicine - April 14, 2016 Category: Statistics Authors: Theresa Dankowski, Andreas Ziegler Tags: Research Article Source Type: research

Group sequential designs with prospectively planned rules for subpopulation enrichment
We propose a class of randomized trial designs aimed at gaining the advantages of wider generalizability and faster recruitment while mitigating the risks of including a population for which there is greater a priori uncertainty. We focus on testing null hypotheses for the overall population and a predefined subpopulation. Our designs have preplanned rules for modifying enrollment criteria based on data accrued at interim analyses. For example, enrollment can be restricted if the participants from a predefined subpopulation are not benefiting from the new treatment. Our designs have the following features: the multiple tes...
Source: Statistics in Medicine - April 12, 2016 Category: Statistics Authors: Michael Rosenblum, Brandon Luber, Richard E. Thompson, Daniel Hanley Tags: Research Article Source Type: research

A Review of Techniques for Detection of Movement Intention Using Movement-Related Cortical Potentials.
In this study, we recapitulate the features such as signal's acquisition, processing, and enhancement and different electrode montages used for EEG data recoding from different studies that used MRCPs to predict the upcoming real or imaginary movement. An authentic identification of human movement intention, accompanying the knowledge of the limb engaged in the performance and its direction of movement, has a potential implication in the control of external devices. This information could be helpful in development of a proficient patient-driven rehabilitation tool based on brain-computer interfaces (BCIs). Such a BCI parad...
Source: Computational and Mathematical Methods in Medicine - February 19, 2016 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Group sequential control of overall toxicity incidents in clinical trials - non-Bayesian and Bayesian approaches
In some small clinical trials, toxicity is not a primary endpoint; however, it often has dire effects on patients’ quality of life and is even life-threatening. For such clinical trials, rigorous control of the overall incidence of adverse events is desirable, while simultaneously collecting safety information. In this article, we propose group sequential toxicity monitoring strategies to control overall toxicity incidents below a certain level as opposed to performing hypothesis testing, which can be incorporated into an existing study design based on the primary endpoint. We consider two sequential methods: a non-B...
Source: Statistical Methods in Medical Research - February 16, 2016 Category: Statistics Authors: Yu, J., Hutson, A. D., Siddiqui, A. H., Kedron, M. A. Tags: Articles Source Type: research

Time‐varying effect modeling with longitudinal data truncated by death: conditional models, interpretations, and inference
Recent studies found that infection‐related hospitalization was associated with increased risk of cardiovascular (CV) events, such as myocardial infarction and stroke in the dialysis population. In this work, we develop time‐varying effects modeling tools in order to examine the CV outcome risk trajectories during the time periods before and after an initial infection‐related hospitalization. For this, we propose partly conditional and fully conditional partially linear generalized varying coefficient models (PL‐GVCMs) for modeling time‐varying effects in longitudinal data with substantial follow‐up truncation ...
Source: Statistics in Medicine - December 9, 2015 Category: Statistics Authors: Jason P. Estes, Danh V. Nguyen, Lorien S. Dalrymple, Yi Mu, Damla Şentürk Tags: Research Article Source Type: research

Statistical methods for studying disease subtype heterogeneity
A fundamental goal of epidemiologic research is to investigate the relationship between exposures and disease risk. Cases of the disease are often considered a single outcome and assumed to share a common etiology. However, evidence indicates that many human diseases arise and evolve through a range of heterogeneous molecular pathologic processes, influenced by diverse exposures. Pathogenic heterogeneity has been considered in various neoplasms such as colorectal, lung, prostate, and breast cancers, leukemia and lymphoma, and non‐neoplastic diseases, including obesity, type II diabetes, glaucoma, stroke, cardiovascular d...
Source: Statistics in Medicine - December 1, 2015 Category: Statistics Authors: Molin Wang, Donna Spiegelman, Aya Kuchiba, Paul Lochhead, Sehee Kim, Andrew T. Chan, Elizabeth M. Poole, Rulla Tamimi, Shelley S. Tworoger, Edward Giovannucci, Bernard Rosner, Shuji Ogino Tags: Tutorial in Biostatistics Source Type: research

Bayesian inference for an illness-death model for stroke with cognition as a latent time-dependent risk factor
Longitudinal data can be used to estimate the transition intensities between healthy and unhealthy states prior to death. An illness-death model for history of stroke is presented, where time-dependent transition intensities are regressed on a latent variable representing cognitive function. The change of this function over time is described by a linear growth model with random effects. Occasion-specific cognitive function is measured by an item response model for longitudinal scores on the Mini-Mental State Examination, a questionnaire used to screen for cognitive impairment. The illness-death model will be used to identi...
Source: Statistical Methods in Medical Research - November 26, 2015 Category: Statistics Authors: van den Hout, A., Fox, J.-P., Klein Entink, R. H. Tags: Articles Source Type: research