Socr news isi wsc ips35 fetal anoxia definition 2019 – socr

Petabytes of imaging, clinical, biospecimen, genetics and phenotypic biomedical data are acquired annually. Tens-of-thousands of new methods and computational algorithms are developed and fetal anoxia definition reported in the literature and thousands of software tools and fetal anoxia definition data analytic services are introduced each year. This imaging statistics and predictive data analytics session will include fetal anoxia definition presentations of leading experts in biomedical imaging, computational neuroscience, and statistical learning focused on streamlining big biomedical data methodologies fetal anoxia definition as well as techniques for management, aggregation, manipulation, computational modeling, and statistical inference.


The session will blend innovative model-based and model-free techniques for representation, analysis and interpretation of large, heterogeneous, multi-source, incomplete and incongruent imaging and phenotypic data elements.

• the digital revolution demands substantial quantitative skills, data-literacy, and analytical competence: health science doctoral programs need to be revised and expanded fetal anoxia definition to build basic-science (STEM) expertise, emphasize team-science, rely on holistic understanding of biomedical systems and health problems, and amplify dexterous abilities to handle, interrogate and interpret complex multisource information.

This talk will present some of the big neuroscience data fetal anoxia definition research and education challenges and opportunities. Specifically, we will identify the core characteristics of complex neuroscience data, discuss strategies for data harmonization and aggregation, and show case-studies using large normal and pathological cohorts. Examples of methods that will be demonstrated include datasifter (enabling secure sharing of data), compressive big data analytics (facilitating inference on multi-source heterogeneous datasets), and model-free prediction (forecasting of clinical features or derived computed phenotypes). Simulated data as well as clinical data (UK biobank, alzheimer’s disease neuroimaging initiative, and amyotrophic lateral sclerosis case-studies) will be used for testing and validation of the techniques. In support of open-science, result reproducibility, and methodological improvements, all datasets, statistical methods, computational algorithms, and software tools are freely available online.

The challenge of making comparison of brain networks and multimodal fetal anoxia definition brain imaging data between healthy and diseased cohorts lies in fetal anoxia definition the high dimensionality of brain imaging data. To make statistically significant claims while avoiding false positives and fetal anoxia definition false negatives, prohibitively large sample sizes are needed. This is the main disadvantage of the current framework for fetal anoxia definition hypothesis testing. T-tests, mann-whitney and similar hypothesis testing methods using point statistics make fetal anoxia definition model based assumptions of data that cluster around a mean fetal anoxia definition value. Significance is ascertained after ascribing sufficiently improbable difference in means fetal anoxia definition or variance between cohorts. Even when statistically significant differences can be ascribed, there is a lack of usable hypothesis that can grant fetal anoxia definition insight into the nature of these differences. We propose a novel approach to comparing high dimensional brain fetal anoxia definition imaging datasets such as brain networks. We suggest that deep learning algorithms could be applied to fetal anoxia definition create generative models of the underlying dataset which is a fetal anoxia definition type of hypothesis on the data from each cohort. Using different deep learning architectures, training algorithms, or different instances of trained networks, we can generate multiple hypothesis / generative models of the underlying datasets. A family of hypothesis / generative models of a given cohort dataset specifies a bound fetal anoxia definition on possible hypothesis for the data. Collecting more brain datasets essentially prunes the hypothesis space and fetal anoxia definition shrinks the boundaries of plausible models. We further propose that the family of generative models from fetal anoxia definition different cohorts can be compared via measures of statistical dissimilarity fetal anoxia definition using statistical distance metrics such as the fisher information metric. Generative models as hypothesis on datasets permit further interaction which fetal anoxia definition allows researchers to learn the meaning of each hypothesis, thus adding value and insight to analysis.

Big data provide a playground for researchers to address extremely fetal anoxia definition interesting and novel questions important to deriving a better understanding fetal anoxia definition of both optimal and suboptimal brain health. However, the breadth of available information is also associated with considerable fetal anoxia definition risks when not handled properly. Additionally, despite all of the data that is at our fingertips, sometimes covariate data are missing. This talk will discuss approaches to dealing with large numbers fetal anoxia definition of variables involved in big data, and will address different strategies for inference testing (correction for multiple testing) in genetic, epigenetic, and neuroimaging data. Further, the talk will cover the different instances of missing covariate fetal anoxia definition data and will describe approaches to deal with these missing fetal anoxia definition data. Audience interaction will take place with short quizzes throughout the fetal anoxia definition talk.

In the neuroimaging literature, the default mode network (DMN) refers to a group of areas in the human cerebral fetal anoxia definition cortex that consistently shows decreased activity in attention-demanding tasks and increased activity under resting-state with eyes-closed or with simple visual fixation. The discovery of DMN has boosted research interest in self-referential or intrinsic activity in the brain in both patients fetal anoxia definition and healthy controls. Since 1997, related studies have mainly relied on the group-averaged responses or seed-based correlations to identify increased/decreased activity in the DMN areas. In this study, we conducted a resting-state experiment by considering the eyes-closed and eyes-open conditions, and by particularly analyzing the reproducible activity across subjects in fetal anoxia definition the DMN areas (areas 8, 9, 10, 20, 23, 24, 25, 31, 32, 39, 40 and the entorhinal cortex). The reproducible activity was estimated using the standardized intraclass-correlations (iccs); the statistical thresholding of the ICC maps was done by fetal anoxia definition considering the non-stationarity of on-going BOLD signals during the resting-state conditions. The DMN areas were parcellated according the jubrain cytoarchitectonic atlas. Forty-nine right-handed adults (26 females, averaged age: 23.08±3.188 years) participated the resting-state task involving 4 min eyes-closed followed by 4 min eyes-open. The MRI scan was performed using a 3T MAGNETOM skyra fetal anoxia definition scanner and a standard 20-channel head-neck coil. The echo planar imaging (EPI) scans were acquired with parameters TR/TE = 2000 ms/30 ms, flip angle = 84°, 35 slices, slice thickness = 3.4 mm, FOV = 192 mm, and resolution 3x3x3.74 mm to cover the whole brain including the cerebellum. The results suggested that a variety of brain activity could fetal anoxia definition be found in the DMN areas including short-term increased/decreased activity after the eyes-closed/open instructions. We suggest being cautious in using the DMN in cognitive fetal anoxia definition and clinical studies.

Nowadays a large amount of data is available, and the need for novel statistical strategies to analyze such fetal anoxia definition data sets is pressing. This talk focuses on the development of statistical and computational fetal anoxia definition strategies for a sparse regression model in the presence of fetal anoxia definition mixed signals. The existing estimation methods have often ignored contributions from weak fetal anoxia definition signals resulting in biased selection and prediction. However, in reality, many predictors altogether provide useful information for prediction, although the amount of such useful information in a single fetal anoxia definition predictor might be modest. The search for such signals, sometimes called networks or pathways, is for instance an important topic for those working on fetal anoxia definition personalized medicine. We discuss a new “post selection shrinkage estimation strategy” that takes into account the joint impact of both strong fetal anoxia definition and weak signals to improve the prediction accuracy, and opens pathways for further research in such scenarios.

Ivo D. Dinov is a professor of health behavior and biological sciences fetal anoxia definition and computational medicine and bioinformatics at the university of michigan. He directs the statistics online computational resource and co-directs the center for complexity and self-management of chronic disease ( CSCD) and the multi-institutional probability distributome project. Dr. Dinov serves as associate director of the michigan institute for fetal anoxia definition data science (MIDAS) and associate director of the university of michigan neuroscience graduate fetal anoxia definition program. He is a member of the american statistical association (ASA), the international association for statistical education (IASE), the american mathematical society, the american medical informatics association (AMIA), as well as an elected member of the international statistical fetal anoxia definition institute (ISI).

Eric ho tatt wei is a senior lecturer at universiti fetal anoxia definition teknologi petronas, as well as a malaysia node coordinator of the international fetal anoxia definition neuroinformatics coordinating facility (INCF). He received his msc and phd degrees in electrical engineering fetal anoxia definition from stanford university, USA. During his phd, he developed an automated robotic system to manipulate fruit flies fetal anoxia definition for live brain imaging. Back in malaysia, he worked on the development of microfluidic devices for monitoring fetal anoxia definition and manipulating blood cells for immunotherapy in low resource settings. His current research interests are in developing novel tools at fetal anoxia definition the intersection of deep learning, brain sciences and networks and he is applying these techniques fetal anoxia definition to characterize the effect of addiction and aging on the fetal anoxia definition brain as well as to enhance the efficacy of brain fetal anoxia definition interventions to improve cognition

Dr. Qiu is dean’s chair associate professor at department of biomedical engineering and fetal anoxia definition clinical imaging research centre at national university of singapore. She is also a principal investigator at singapore institute for fetal anoxia definition clinical sciences of agency for science technology and research (A*STAR). Dr. Qiu received her BS in biomedical engineering from tsinghua university fetal anoxia definition in 1999, MS degrees in biomedical engineering and applied mathematics and statistics fetal anoxia definition from university of connecticut in 2002 and from the johns fetal anoxia definition hopkins university in 2005, respectively. She obtained her phd degree at the johns hopkins university fetal anoxia definition in 2006. After one-year postgraduate training, she joined the national university of singapore as assistant professor fetal anoxia definition and launched her own laboratory for medical image data sciences fetal anoxia definition at both the faculty of engineering and the school of fetal anoxia definition medicine. Dr. Qiu has been devoted to innovation in computational analyses of fetal anoxia definition complex and informative datasets comprising of disease phenotypes, neuroimage, and genetic data to understand the origins of individual differences fetal anoxia definition in health throughout the lifespan. She received faculty young research award, 2016 young researcher award of NUS. She has recently been appointed as endowed “dean’s chair” associate professor to honor her outstanding research achievements. She serves on the program committee of organization of human fetal anoxia definition brain mapping and editor of the journals neuroimage and frontiers fetal anoxia definition in neuroscience.

Prof. Ahmed is dean of the brock university school of mathematics fetal anoxia definition and statistics. Prior to that, he was head of mathematics at the university of windsor fetal anoxia definition and university of regina. He is a fellow of american statistical association and an fetal anoxia definition elected member of the international statistical institute. Dr. Ahmed is an expert in statistical inference, shrinkage estimation, and asymptotic theory. He serves on the editorial boards of many statistical journals fetal anoxia definition and served as a board of director and chairman of fetal anoxia definition the education committee of the statistical society of canada. Dr. Ahmed is a member of an evaluation group, discovery grants and the grant selection committee, natural sciences and engineering research council of canada (NSERC).

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