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At least 109 records · Page 6Linked to original sources
PubMed1990

Quantified neurophysiology with mapping: statistical inference, exploratory and confirmatory data analysis.

Topographic mapping of brain electrical activity has become a commonly used method in the clinical as well as research laboratory. To enhance analytic power and accuracy, mapping applications often involve statistical paradigms for the detection of abnormality or difference. Because mapping studies involve many measurements and variables, the appearance of a large data dimensionality may be created. If abnormality is sought by statistical mapping procedures and if the many variables are uncorrelated, certain positive findings could be attributable to chance. To protect against this undesirable possibility we advocate the replication of initial findings on independent data sets. Statistical difference attributable to chance will not replicate, whereas real difference will reproduce. Clinical studies must, therefore, provide for repeat measurements and research studies must involve analysis of second populations. Furthermore, Principal Components Analysis can be employed to demonstrate that variables derived from mapping studies are highly intercorrelated and data dimensionality substantially less than the total number of variables initially created. This reduces the likelihood of capitalization on chance. The need to constrain alpha levels is not necessary when dimensionality is low and/or a second data set is available. When only one data set is available in research applications, techniques such as the Bonferroni correction, the "leave-one-out" method, and Descriptive Data Analysis (DDA) are available. These techniques are discussed, clinical and research examples are given, and differences between Exploratory (EDA) and Confirmatory Data Analysis (EDA) are reviewed.

Brain↗
PubMed1988

The use of a personal computer for trend data analysis with the Ohmeda 3700 pulse oximeter.

The Ohmeda 3700 pulse oximeter provides trend data storage of arterial oxygen saturation (SaO2) and pulse rate measurements for a maximum of 8 hours. This feature allows the oximeter to be used as a stand-alone unit for overnight studies of saturation during sleep. Subsequent transfer and processing of the stored SaO2 data requires additional software. We present a program for data processing that uses the Lotus 1-2-3 program on IBM and compatible microcomputers and that performs a data distribution and statistical analysis on these trend data and presents them in graphic form. Processing SaO2 trend data within the Lotus 1-2-3 worksheet format allows the user to easily add to or modify the program presented here, depending on individual needs.

Adult↗
PubMed1985

Exploratory data analysis and the use of the hazard function for interpreting survival data: an investigator's primer.

This report discusses how one can use the hazard function to gain important insights on the patterns of failure in clinical studies when the principal endpoint is a time metric. These new insights may help gain increased understanding into the pathogenesis of a chronic disease and how it is affected by treatment intervention. The qualitative behavior of the hazard function can reveal whether mortality is increasing, decreasing, or is constant over time. Simple graphic plots are all that is necessary to show characteristic failure patterns. These informal procedures are in the spirit of carrying out exploratory analyses on the data. This report discusses the organization of clinical data using a "branch and leaf" plot, outlines the calculation of the hazard function and life table, and uses examples from lung cancer and uveal melanoma to illustrate calculations and ways of interpreting hazard functions.

Adenocarcinoma↗
PubMed1991

Data analysis of the Second International Workshop on Small Cell Lung Cancer Antigens.

Methods of data collection for the 2nd Small Cell Lung Cancer Workshop are described, and data reliability is reviewed. The method of cluster analysis of the workshop antibodies is described and discussed. Of the 27,111 results submitted 20,705 were judged to be reliable for analysis and 13,802 of these came from immunohistology experiments. Data derived from immunocytochemistry experiments were somewhat less reproducible than flow cytometry, immunohistology and ELISA experiments. The cluster analysis was developed from methods employed in the leucocyte antigens workshops. Several checks on the methods of cluster analysis and the transformation of data did not substantially alter the final groupings. The workshop confirms that, although there are some methodological difficulties, the cluster analysis can successfully be applied to data derived largely from immunohistology, and thus has applicability to other tumour types.

Antibodies, Monoclonal↗
PubMed1986

Longitudinal data analysis for discrete and continuous outcomes.

Longitudinal data sets are comprised of repeated observations of an outcome and a set of covariates for each of many subjects. One objective of statistical analysis is to describe the marginal expectation of the outcome variable as a function of the covariates while accounting for the correlation among the repeated observations for a given subject. This paper proposes a unifying approach to such analysis for a variety of discrete and continuous outcomes. A class of generalized estimating equations (GEEs) for the regression parameters is proposed. The equations are extensions of those used in quasi-likelihood (Wedderburn, 1974, Biometrika 61, 439-447) methods. The GEEs have solutions which are consistent and asymptotically Gaussian even when the time dependence is misspecified as we often expect. A consistent variance estimate is presented. We illustrate the use of the GEE approach with longitudinal data from a study of the effect of mothers' stress on children's morbidity.

Child↗
PubMed1991

Mathematical model of antiviral immune response. I. Data analysis, generalized picture construction and parameters evaluation for hepatitis B.

The present approach to the mathematical modelling of infectious diseases is based upon the idea that specific immune mechanisms play a leading role in development, course, and outcome of infectious disease. The model describing the reaction of the immune system to infectious agent invasion is constructed on the bases of Burnet's clonal selection theory and the co-recognition principle. The mathematical model of antiviral immune response is formulated by a system of ten non-linear delay-differential equations. The delayed argument terms in the right-hand part are used for the description of lymphocyte division, multiplication and differentiation processes into effector cells. The analysis of clinical and experimental data allows one to construct the generalized picture of the acute form of viral hepatitis B. The concept of the generalized picture includes a quantitative description of dynamics of the principal immunological, virological and clinical characteristics of the disease. Data of immunological experiments in vitro and experiments on animals are used to obtain estimates of permissible values of model parameters. This analysis forms the bases for the solution of the parameter identification problem for the mathematical model of antiviral immune response which will be the topic of the following paper (Marchuk et al., 1991, J. theor. Biol. 15).

Hepatitis B↗
PubMed1989

Comparison of the data, analysis, and results of X-ray absorption studies of cytochrome c oxidase.

Differences in the methods of analysis of X-ray absorption data used by Powers et al. [Powers, L., Blumberg, W. E., Chance, B., Barlow, C., Leigh, J., Jr., Smith, J., Yonetani, T., Vik, S., & Peisach, J. (1979) Biochim. Biophys. Acta 547, 520-538; Powers, L., Chance, B., Ching, Y., & Angiolillo, P. (1981) Biophys. J. 34, 465-498] and Scott et al. [Scott, R., Schwartz, J., & Cramer S. (1986) Biochemistry 25, 5546-5555] are clarified. In addition, we compare the X-ray absorption data and results for resting cytochrome c oxidase reported by both groups using the same analysis method and conclude apart from any assumptions that the data are not identical.

Copper↗
PubMed1979

Some applications of categorical data analysis to epidemiological studies.

Several examples of categorized data from epidemiological studies are analyzed to illustrate that more informative analysis than tests of independence can be performed by fitting models. All of the analyses fit into a unified conceptual framework that can be performed by weighted least squares. The methods presented show how to calculate point estimate of parameters, asymptotic variances, and asymptotically valid chi 2 tests. The examples presented are analysis of relative risks estimated from several 2 x 2 tables, analysis of selected features of life tables, construction of synthetic life tables from cross-sectional studies, and analysis of dose-response curves.

Actuarial Analysis↗
PubMed1986

Real-time acquisition and data analysis of skeletal muscle contraction in a multi-user environment.

A data acquisition system is described which acquires data from contracting skeletal muscle. The system is designed to run in a multi-user environment while acquiring contractile data in real-time. Time dedicated solely to laboratory experiments is thus eliminated. A menu-driver is included to allow users to enter experimental commands with or without command arguments. Error monitoring functions prevent operator errors from causing data loss. Data storage in both ASCII and binary formats maximizes file flexibility, readability and accessibility. Finally, an on-line tutorial and help facility is provided for user training. The system developed is applicable to any experimental environment involving data acquisition, storage and analysis.

Animals↗
PubMed1991

[Computer-assisted data analysis of injuries of the skeletal system in polytrauma patients].

The data of 366 patients with multiple injuries were evaluated by application of data processing over a period of seven years. Age and sex distribution, location and combination of injuries, mortality, mechanism of accident, diagnostics as well as therapy were analysed. 91.3% of our patients had injuries of the skeleton. The male to female ratio was 2:1. In 55.4% the age of the patients ranged from 10 to 39 years. The mortality rate of all patients was 27.2%. In the third decade only 16.9% of the patients died. Whereas the mortality of the patients in the 1. decade as well as between the 7. and 9. decades of life was very high (33% and 50%). Most of the skeletal injuries were located in the shank (24% open fractures). The mortality rate increases with the number of injuries (Table III). Patients with concomitant injuries, such as head injuries and fractures of the extremities were the most common combination of multiple injuries. 20% of the patients in this group died. Patients with combined injuries of the head, chest, abdomen and skeleton had highest mortality (57%). X-ray examination of the skull, chest, extremities and mainly of the spine and pelvis should be subjects of routine diagnostics. In patients who were suspected of having a blunt abdominal trauma, the first diagnostic technique will be ultrasound. On account of the various number of concomitant injuries as well as the patients individuality, the estimation of prognosis by systems for the classification of the severity of injury is fraught with difficulties. The analysis of the evaluated data showed that previously small number of variables may predict the prognosis of the course of disease.

Adolescent↗
PubMed2026

OmicsQ: a user-friendly platform for interactive quantitative omics data analysis.

MOTIVATION: High-throughput omics technologies generate complex datasets with thousands of features that are quantified across multiple experimental conditions, but often suffer from incomplete measurements, missing values, and individually fluctuating variances. This requires analytical tools for accurate, deep and insightful biological interpretation, capable of dealing with a large variety of data properties and different amounts of completeness. Software capable of handling such data complexity and integrating with external applications for downstream analysis remains rare and mostly relies on programming-based environments, limiting accessibility for researchers without computational expertise. RESULTS: We present OmicsQ, an interactive, web-based platform designed to streamline quantitative omics data analysis. OmicsQ provides an intuitive, browser-based visualization interface that integrates established statistical processing tools. Those include robust batch correction, automated experimental design annotation, and handling of missing data without imputation, which maintains data integrity and avoids artifacts from a priori assumptions. OmicsQ seamlessly interacts with external applications (e.g. PolySTest, VSClust, ComplexBrowser) for statistical testing, clustering, analysis of protein complex behavior, and pathway enrichment, offering a comprehensive and flexible workflow from data import to biological interpretation that is broadly applicable across domains. AVAILABILITY AND IMPLEMENTATION: OmicsQ is implemented in R and Shiny and is available at https://computproteomics.bmb.sdu.dk/app_direct/OmicsQ. Source code and installation instructions: https://github.com/computproteomics/OmicsQ, DOI: 10.5281/zenodo.17778420.

Software↗
PubMed1990

[Documentation of the surgical report with graphic statistical data analysis--a simplification of daily routine work].

A data collection system on microcomputer connected with an automatic medical report system for operations, was developed to facilitate both medical report as well as documentation. Linking different commercial software products by use of a Pascal programme, we were able to speed up daily routine work as well as establish efficient graphical statistics of patient data.

Cesarean Section↗
PubMed2025

Multimodal CustOmics: A unified and interpretable multi-task deep learning framework for multimodal integrative data analysis in oncology.

Characterizing cancer presents a delicate challenge as it involves deciphering complex biological interactions within the tumor's microenvironment. Clinical trials often provide histology images and molecular profiling of tumors, which can help understand these interactions. Despite recent advances in representing multimodal data for weakly supervised tasks in the medical domain, achieving a coherent and interpretable fusion of whole slide images and multi-omics data is still a challenge. Each modality operates at distinct biological levels, introducing substantial correlations between and within data sources. In response to these challenges, we propose a novel deep-learning-based approach designed to represent multi-omics & histopathology data for precision medicine in a readily interpretable manner. While our approach demonstrates superior performance compared to state-of-the-art methods across multiple test cases, it also deals with incomplete and missing data in a robust manner. It extracts various scores characterizing the activity of each modality and their interactions at the pathway and gene levels. The strength of our method lies in its capacity to unravel pathway activation through multimodal relationships and to extend enrichment analysis to spatial data for supervised tasks. We showcase its predictive capacity and interpretation scores by extensively exploring multiple TCGA datasets and validation cohorts. The method opens new perspectives in understanding the complex relationships between multimodal pathological genomic data in different cancer types and is publicly available on Github.

Deep Learning↗
PubMed1988

Objective comparison of exon and intron sequences by means of 2-dimensional data analysis methods.

Here we advocate the use of 2-dimensional data representation in the context of the informational approach of sequence analysis (Claverie & Bougueleret (1986) Nucleic Acids Research 14, 179-196) by applying these methods to the problem of intron/exon discrimination. Two main findings are reported: i) oligonucleotide patterns complementary to the Ul small nuclear RNA are specifically avoided in exon sequences, ii) vertebrate intron sequences, to the exclusion of other eukaryotic phyla, are characterized by a peculiar distribution of CpG containing patterns.

Algorithms↗