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Results for “Data integration”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

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At least 91 records · Page 5Linked to original sources
PubMed2003

Three-dimensional visualization of the craniofacial patient: volume segmentation, data integration and animation.

The research goal at the Craniofacial Virtual Reality Laboratory of the School of Dentistry in conjunction with the Integrated Media Systems Center, School of Engineering, University of Southern California, is to develop computer methods to accurately visualize patients in three dimensions using advanced imaging and data acquisition devices such as cone-beam computerized tomography (CT) and mandibular motion capture. Data from these devices were integrated for three-dimensional (3D) patient-specific visualization, modeling and animation. Generic methods are in development that can be used with common CT image format (DICOM), mesh format (STL) and motion data (3D position over time). This paper presents preliminary descriptive studies on: 1) segmentation of the lower and upper jaws with two types of CT data--(a) traditional whole head CT data and (b) the new dental Newtom CT; 2) manual integration of accurate 3D tooth crowns with the segmented lower jaw 3D model; 3) realistic patient-specific 3D animation of the lower jaw.

Cineradiography↗
PubMedDate not supplied

HyperCard to SPSS: improving data integrity.

This article describes a database design that captures responses in a HyperCard stack and moves the data to SPSS for the Macintosh without the need to rekey data. Pregnant women used an interactive computer application with a touch screen to answer questions and receive educational information about fetal alcohol syndrome. A database design was created to capture survey responses through interaction with a computer by a sample of prenatal women during formative evaluation trials. The author does not compare this method of data collection to other methods. This article simply describes the method of data collection as a useful research tool.

Computer-Assisted Instruction↗
PubMed2006

ARIA2: automated NOE assignment and data integration in NMR structure calculation.

UNLABELLED: Modern structural genomics projects demand for integrated methods for the interpretation and storage of nuclear magnetic resonance (NMR) data. Here we present version 2.1 of our program ARIA (Ambiguous Restraints for Iterative Assignment) for automated assignment of nuclear Overhauser enhancement (NOE) data and NMR structure calculation. We report on recent developments, most notably a graphical user interface, and the incorporation of the object-oriented data model of the Collaborative Computing Project for NMR (CCPN). The CCPN data model defines a storage model for NMR data, which greatly facilitates the transfer of data between different NMR software packages. AVAILABILITY: A distribution with the source code of ARIA 2.1 is freely available at http://www.pasteur.fr/recherche/unites/Binfs/aria2.

Algorithms↗
PubMed2005

Integrated data acquisition and processing to determine metabolite contents, relaxation times, and macromolecule baseline in single examinations of individual subjects.

Absolute quantitation of clinical (1)H-MR spectra is virtually always incomplete for single subjects because the separate determination of spectrum, baseline, and transverse and longitudinal relaxation times in single subjects is prohibitively long. Integrated Processing and Acquisition of Data (IPAD) based on a combined 2-dimensional experimental and fitting strategy is suggested to substantially improve the information content from a given measurement time. A series of localized saturation-recovery spectra was recorded and combined with 2-dimensional prior-knowledge fitting to simultaneously determine metabolite T(1) (from analysis of the saturation-recovery time course), metabolite T(2) (from lineshape analysis based on metabolite and water peak shapes), macromolecular baseline (based on T(1) differences and analysis of the saturation-recovery time course), and metabolite concentrations (using prior knowledge fitting and conventional procedures of absolute standardization). The procedure was tested on metabolite solutions and applied in 25 subjects (15-78 years old). Metabolite content was comparable to previously found values. Interindividual variation was larger than intraindividual variation in repeated spectra for metabolite content as well as for some relaxation times. Relaxation times were different for various metabolite groups. Parts of the interindividual variation could be explained by significant age dependence of relaxation times.

Adolescent↗
PubMed2005

Pathology data integration with eXtensible Markup Language.

It is impossible to overstate the importance of XML (eXtensible Markup Language) as a data organization tool. With XML, pathologists can annotate all of their data (clinical and anatomic) in a format that can transform every pathology report into a database, without compromising narrative structure. The purpose of this manuscript is to provide an overview of XML for pathologists. Examples will demonstrate how pathologists can use XML to annotate individual data elements and to structure reports in a common format that can be merged with other XML files or queried using standard XML tools. This manuscript gives pathologists a glimpse into how XML allows pathology data to be linked to other types of biomedical data and reduces our dependence on centralized proprietary databases.

Database Management Systems↗
PubMed1998

Integrated data system means better maintenance.

The University of Texas M.D. Anderson Cancer Center has consolidated six databases into one integrated facilities management system. In the first year of implementation, the system has saved about $150,000 by cutting personel costs and reducing inventory by 27%. Keys to successful implementation include completely shutting off the old system before starting up the new one and testing the system in-house to work out glitches before it went on-line.

Academic Medical Centers↗
PubMedDate not supplied

HEDIS data integrity.

Explore the source record for details and available documents.

Centers for Medicare and Medicaid Services, U.S.↗
PubMed2025

CrossAttOmics: multiomics data integration with cross-attention.

MOTIVATION: Advances in high throughput technologies enabled large access to various types of omics. Each omics provides a partial view of the underlying biological process. Integrating multiple omics layers would help have a more accurate diagnosis. However, the complexity of omics data requires approaches that can capture complex relationships. One way to accomplish this is by exploiting the known regulatory links between the different omics, which could help in constructing a better multimodal representation. RESULTS: In this article, we propose CrossAttOmics, a new deep-learning architecture based on the cross-attention mechanism for multiomics integration. Each modality is projected in a lower dimensional space with its specific encoder. Interactions between modalities with known regulatory links are computed in the feature representation space with cross-attention. The results of different experiments carried out in this article show that our model can accurately predict the types of cancer by exploiting the interactions between multiple modalities. CrossAttOmics outperforms other methods when there are few paired training examples. Our approach can be combined with attribution methods like LRP to identify which interactions are the most important. AVAILABILITY AND IMPLEMENTATION: The code is available at https://github.com/Sanofi-Public/CrossAttOmics and https://doi.org/10.5281/zenodo.15065928. TCGA data can be downloaded from the Genomic Data Commons Data Portal. CCLE data can be downloaded from the depmap portal.

Humans↗
PubMed2005

Data integrity: backup.

School nurses and health office staff have an ethical and legal obligation to protect the integrity of electronic student health records. Various sources, both accidental and malicious, can threaten student health data. School nurses must employ regular and reliable methods to back up student health data.

Attitude to Computers↗
PubMed1989

The phenomenology of spatial integration: data and models.

A briefly presented visual stimulus followed by darkness seems to persist beyond its physical offset. We are concerned here with the relation between two characteristics of this visible persistence: first, its phenomenological resemblance to the stimulus that spawned it and second, its usefulness as a basis for integrating visual stimuli that are separated in time. We describe two experiments using a task in which two halves of a visual stimulus were presented successively and observers reported how complete the stimulus appeared to be. Stimuli appeared less complete with increases in both the duration of the interval intervening between presentation of the two halves and the duration of the initially presented stimulus half. This data pattern is similar to that obtained in tasks in which spatial integration of two temporally disparate stimuli is necessary for correct responding. On the basis of this similarity, we argue that phenomenological appearance and ability to integrate stimuli over time are two facets of the same perceptual events. We describe a formal model to account for these and other data.

Adult↗
PubMed2005

Determining sexual dimorphism in frog measurement data: integration of statistical significance, measurement error, effect size and biological significance.

Several analytic techniques have been used to determine sexual dimorphism in vertebrate morphological measurement data with no emergent consensus on which technique is superior. A further confounding problem for frog data is the existence of considerable measurement error. To determine dimorphism, we examine a single hypothesis (Ho = equal means) for two groups (females and males). We demonstrate that frog measurement data meet assumptions for clearly defined statistical hypothesis testing with statistical linear models rather than those of exploratory multivariate techniques such as principal components, correlation or correspondence analysis. In order to distinguish biological from statistical significance of hypotheses, we propose a new protocol that incorporates measurement error and effect size. Measurement error is evaluated with a novel measurement error index. Effect size, widely used in the behavioral sciences and in meta-analysis studies in biology, proves to be the most useful single metric to evaluate whether statistically significant results are biologically meaningful. Definitions for a range of small, medium, and large effect sizes specifically for frog measurement data are provided. Examples with measurement data for species of the frog genus Leptodactylus are presented. The new protocol is recommended not only to evaluate sexual dimorphism for frog data but for any animal measurement data for which the measurement error index and observed or a priori effect sizes can be calculated.

Analysis of Variance↗
PubMed2026

Multimodal artificial intelligence and machine learning in oncology: from data integration to precision cancer care.

Cancer remains a major global health burden, with approximately 20 million new cases and 9.7 million cancer-related deaths reported globally in 2022. While advances in radiological imaging, molecular profiling, and clinical data have enhanced the interpretation of disease progression, the availability of multiple such modalities still does not meet the needs of a large patient population. This narrative review focuses on the role of multimodal artificial intelligence and machine learning in bridging the gap in interpreting heterogeneous modalities to improve risk prediction, prognostic assessment, and treatment decision-making in precision oncology. Multimodal frameworks such as Pathomic Fusion illustrate how complementary histopathological and genomic information can be integrated for cancer diagnosis and prognostic modeling. Multimodal models have demonstrated potential in virtual biopsy, cancer screening, prognostic prediction, radiotherapy planning, intraoperative guidance, and clinical-trial design using digital twins and synthetic control arms. The major limitations of incorporating multimodal artificial intelligence and machine learning in oncology include data heterogeneity, demographic or institutional biases, and reproducibility challenges that hinder translation. Accordingly, appropriate data-governance strategies, fairness audits, and privacy-preserving approaches such as federated learning should be considered where appropriate. Future progress will depend on the development of standardized benchmarking datasets, robust external validation, seamless integration with electronic health records and picture archiving and communication systems, and the implementation of explainable, secure, and clinically validated multimodal artificial intelligence frameworks that support precision oncology in routine clinical practice.

deep learning↗
PubMed2001

XML, bioinformatics and data integration.

MOTIVATION: The eXtensible Markup Language (XML) is an emerging standard for structuring documents, notably for the World Wide Web. In this paper, the authors present XML and examine its use as a data language for bioinformatics. In particular, XML is compared to other languages, and some of the potential uses of XML in bioinformatics applications are presented. The authors propose to adopt XML for data interchange between databases and other sources of data. Finally the discussion is illustrated by a test case of a pedigree data model in XML. CONTACT: Emmanuel.Barillot@infobiogen.fr

Computational Biology↗
PubMed2003

Data integration and warehousing: coordination between newborn screening and related public health programs.

At birth, patient demographic and health information begin to accumulate in varied databases. There are often multiple sources of the same or similar data. New public health programs are often created without considering data linkages. Recently, newborn hearing screening (NHS) programs and immunization programs have virtually ignored the existence of newborn dried blood spot (DBS) newborn screening databases containing similar demographic data, creating data duplication in their 'new' systems. Some progressive public health departments are developing data warehouses of basic, recurrent patient information, and linking these databases to other health program databases where programs and services can benefit from such linkages. Demographic data warehousing saves time (and money) by eliminating duplicative data entry and reducing the chances of data errors. While newborn screening data are usually the first data available, they should not be the only data source considered for early data linkage or for populating a data warehouse. Birth certificate information should also be considered along with other data sources for infants that may not have received newborn screening or who may have been born outside of the jurisdiction and not have birth certificate information locally available. This newborn screening serial number provides a convenient identification number for use in the DBS program and for linking with other systems. As a minimum, data linkages should exist between newborn dried blood spot screening, newborn hearing screening, immunizations, birth certificates and birth defect registries.

Birth Certificates↗