PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “data integration”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19Linked to original sources
PubMed1999

Telemedicine and terminology: different needs of context information.

Traditionally, communication between healthcare providers, including the provision of physicians with information and knowledge, works quite well because there are implicitly common conventions and assumptions in the collaboration of all involved actors. The basic prerequisite of the communication process between humans is a mutual agreement on syntax and semantics of oral and written language, i.e., of the medical sublanguage. With telemedicine, i.e., the use of telecommunication and informatics in medicine, this prerequisite is no longer sufficient. First, various professionals from different clinical communities, characterized by specialty, nationality, school, etc., share the management of the patient's health. Second, electronically communicated information is more and more intended for processing by computer applications rather than for direct interpretation by human users. Third, the interconnection of distributed heterogeneous software systems in medicine raises the issue of semantic interoperability, especially the problem of data integration. A faithful communication in such a scenario must be based on explicit assumptions "behind" a message. Interpreting an usually highly context-dependent utterance demands for mechanisms on a pragmatic level in natural language processing. The need for additional processing and integration of the transferred data by the receiving system demands for standardization and mediation, taking into consideration contextual knowledge that cannot entirely be explained and processed with linguistic and terminological approaches. This paper describes different categories of contexts and also different needs of applications concerning "context awareness."

Telemedicine↗
PubMed2006

Advancing patient care: integrating new data.

Physicians involved in the management of patients with chronic hepatitis B infection are frequently faced with complex clinical issues concerning the diagnosis, investigation, and treatment of patients. Guidelines exist within the literature that help with decision making; however, in practice individual nuances are often encountered necessitating decisions that go beyond the current guidelines. Following presentation of the available data, a panel of expert hepatologists and gastroenterologists sought to identify and solve challenges that are faced by clinicians in the daily management of patients with chronic hepatitis B infection. The following summary provides an overview of the outcome of these discussions. Because of the complexities of clinical management, the recommendations reflect the opinion of the majority; however, many recommendations were not unanimous. Furthermore, the recommendations that follow are limited to adult patients; the treatment of children was not discussed. A number of issues were identified, and statements concerning possible management strategies that could be applied were developed.

Hepatitis B, Chronic↗
PubMed2025

A comprehensive integration of data on the association of ITPKC polymorphisms with susceptibility to Kawasaki disease: a meta-analysis.

BACKGROUND: This study aims to conduct a comprehensive meta-analysis of existing research to define clear associations between variations in the ITPKC gene and the risk of developing Kawasaki disease (KD). METHODS: A comprehensive search was conducted across multiple databases, including but not limited to PubMed, Scopus, EMBASE, and CNKI, up to June 1, 2024, to gather relevant information. This search utilized keywords and MeSH terms related to hyperbilirubinemia and genetic factors. The inclusion criteria encompassed original case-control, longitudinal, or cohort studies. Correlations were analyzed as odds ratios (ORs) with 95% confidence intervals (CIs) using Comprehensive Meta-Analysis software. RESULTS: Eighteen case-control studies with 5,434 KD cases and 9,419 controls were analyzed. Of these, ten studies assessed 3,129 KD cases and 6,172 controls for the rs28493229 variant, four examined 1,039 cases and 1,688 controls for the rs2290692 variant, two focused on 595 cases and 820 controls for the rs7251246 variant, and two investigated 671 cases and 739 controls for the rs10420685 variant. Results showed a significant association between the rs28493229 polymorphism and increased KD risk across all five genetic models. Subgroup analysis indicated this polymorphism correlates with KD susceptibility in Asians but not in the Chinese population. In contrast, no associations were found between the rs2290692, rs7251246, and rs10420685 polymorphisms and KD risk. CONCLUSIONS: Our pooled data indicate a significant association between the ITPKC rs28493229 polymorphism's minor allele and an increased risk of developing KD, suggesting this variant may enhance susceptibility. Conversely, SNPs rs2290692, rs7251246, and rs10420685 do not demonstrate a statistically significant relationship with KD.

Humans↗
PubMedDate not supplied

What does Medicare pay for? Disentangling the flow of funds to health care providers.

Many Medicare policies pertain to only part of an expenditure category for which there are publicly available data. Integrating three types of data sources, this DataWatch disaggregates Medicare spending by type of provider. It also disaggregates payments to hospital outpatient departments by type of service. The results reveal a number of patterns obscured by more aggregate figures. For instance, although Medicare pays for most skilled nursing facility (SNF) services through Part A, Part B paid SNFs almost a billion dollars for rehabilitation services in fiscal year 1996. The recipients were not eligible for Part A SNF benefits but were residents of nursing homes.

Fee-for-Service Plans↗
PubMed2025

Multi-Omics and Integrative Analytics in Natural Products Discovery.

Natural products (NPs) have long been an essential source of new bioactive compounds for drug discovery; however, traditional methods for screening and isolating these compounds can be slow and often yield diminishing returns. Fortunately, advanced multi-omics and computational approaches present powerful solutions to these challenges. This review highlights innovative methodologies that integrate metabolomics, genomics, transcriptomics, and proteomics with bioinformatics and analytical chemistry to accelerate NP discovery. For instance, untargeted metabolomics platforms like high-resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS) and Global Natural Products Social (GNPS) molecular networking allow for comprehensive profiling of new compounds, while targeted isotope-labeling strategies enhance this process. Additionally, genome and metagenome mining tools such as antibiotics and secondary metabolite analysis shell (antiSMASH), Deep Biosynthetic Gene Cluster (DeepBGC), and Pipeline for Reconstructing Integrated Syntheses of Metabolites (PRISM) quickly identify biosynthetic gene clusters (BGCs) in both cultured and uncultured organisms, often using heterologous expression to validate products. Transcriptomic analyses, including RNA sequencing (RNA-seq), co-expression networks, and fluxomics, help clarify how pathways are regulated, while quantitative proteomics techniques like tandem mass tags/isobaric tags for relative and absolute quantitation (TMT/iTRAQ) and label-free methods, along with chemoproteomics approaches such as cellular thermal shift assay and thermal proteome profiling (TPP), uncover molecular targets and their mechanisms of action. This review also places significant emphasis on the role of artificial intelligence (AI) and machine learning (ML) in integrating multi-omics data, spanning activities from constructing gene-metabolite correlation networks to leveraging knowledge graphs and graph neural networks for data fusion and functional prediction. Finally, this review concludes by discussing the synergistic benefits of multi-omics for natural-product discovery, addressing current technical challenges, and exploring future directions toward high-throughput, intelligent data integration for next-generation NP research.

Biological Products↗
PubMed2025

Multi-omics technologies: Novel tools and methods for assessing nerve injury and regeneration.

Recently, with the rapid advancement of multi-omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, new tools and approaches have been introduced for studying nerve injury and regeneration. This review highlights the application and progress of multi-omics in uncovering the mechanisms of nerve injury, guiding the development of regenerative strategies, and promoting clinical translation. By integrating multi-omics datasets, researchers can comprehensively track dynamic molecular changes following nerve injury, including abnormal gene expression, disrupted protein signaling, altered metabolic programs, and shifts in the immune microenvironment. Single-cell multi-omics technologies resolve cellular heterogeneity, revealing the distinct functions of neurons, glial cells, and immune cell subpopulations during the injury response. Spatially resolved transcriptomics maintain the spatial context of lesion and regeneration sites, enabling precise localization for targeted interventions. Multi-omics technologies not only identify key molecular players involved in nerve regeneration but also create opportunities for personalized medicine. Nonetheless, integrating multi-omics data poses technical challenges, including high dimensionality, batch effects, and algorithmic constraints, while ethical concerns related to stem cell therapy and gene editing require stringent oversight. To transition from structural reconstruction to functional remodeling, future research should emphasize artificial intelligence-driven data integration, organ-on-a-chip modeling, and cross-disciplinary collaboration to overcome existing technical barriers and accelerate the clinical application of neuroregenerative therapies.

artificial intelligence↗
PubMed1988

Integrating distributed data processing.

The abundance and sophistication of technology can lead to solutions before a problem is understood. To maintain a proper focus on problem-solving, the second part of this series explains that we must be willing to rethink and redefine existing problems.

Computer Systems↗