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Results for “information integration”

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At least 19 recordsLinked to original sources
PubMed1979

An accountability model for integrating information systems, evaluation mechanisms, and decision making processes in alcohol and drug abuse agencies.

This article has attempted to demonstrate that decision making and evaluation can be carried out in a systematic fashion only if agencies make a commitment to do so, and only if adequate systems are established. The management information system is the most expensive and most sophisticated component of the integrated model presented here. Its existence, in some fashion, is essential to the operation of the model. Contrary to what many managers may believe and practice, the management information system is not in itself the final solution to evaluation. Neither is the evaluation a panacea for all program ills. Evaluation can provide the information required to meet the ever increasing demands for agency or program accountability evaluation can also provide insights for future decisions to change or alter the allocation of resources. Such evaluation must be carefully planned and implemented; and, at the state level, can be successful only if executed in a systematic manner as suggested here. Regardless of the degree of sophistication of any system, it will work only when supported by users in the local treatment centers. If the model employed does little to serve them, it is not a model worth considering. It is with these needs in mind that this model was developed.

Alcoholism↗
PubMed1976

Research data integrity: a result of an integrated information system.

The toxicologic problems of today frequently require long-term, multidisciplinary experimentation involving large numbers of animals. In order to provide the extensive safety evaluation necessary to produce data that can be reasonably extrapolated to humans, automated research support systems have transcended the position of useful tools and have become an integral part of the total design of experimental protocols. For an automated information system to fully represent the reality of the experiment, it must be able to assure integrity, as well as provide for the storage, calculation, and retrieval of data values of the quality and quantity necessary for fulfilling protocol requirements. Guarantees against error and loss of data, in addition to flexibility and easy access, must be an inherent part of the system if the acceptance and condifence of the investigator are to be obtained. This paper discusses the criteria, philosophies, and benefits of integrated data systems that ensure integrity of toxicologic research support.

Computers↗
PubMed1978

Eye movements and integrating information across fixations.

A series of experiments was conducted in which a word or letter string initially appeared in parafoveal vision, followed by the subject's eye movement to the stimulus. During the saccade, the initially displayed stimulus was replaced by a word that the subject was asked to read. The results indicated that the types of prior parafoveal information studied facilitated the naming of the word. The effect was obtained when the subject made an eye movement and when the saccade was simulated. There was also evidence that attentional allocation was tied to the direction of the eye movement.

Eye Movements↗
PubMed1976

An integrated cardiorespiratory pathology information system.

An integrated computer system which is in its initial year of implementation has been developed to handle pathological data of cardiorespiratory organs. On the single entry of data captured at the source, the interactive computer system generates reports for administrative requirements by law, updates a data base of cardiorespiratory histopathological data for research purposes and facilitates inquiry for periodical management reports. The system is based on multiple-source documents which have numerically precoded choice option statements as well as free text provision for those statements where precoded options are not provided. The computer system has replaced manual system procedures most effectively in terms of cost.

Cardiovascular System↗
PubMed2025

A Graph Contrastive Learning Method for Enhancing Genome Recovery in Complex Microbial Communities.

Accurate genome binning is essential for resolving microbial community structure and functional potential from metagenomic data. However, existing approaches-primarily reliant on tetranucleotide frequency (TNF) and abundance profiles-often perform sub-optimally in the face of complex community compositions, low-abundance taxa, and long-read sequencing datasets. To address these limitations, we present MBGCCA, a novel metagenomic binning framework that synergistically integrates graph neural networks (GNNs), contrastive learning, and information-theoretic regularization to enhance binning accuracy, robustness, and biological coherence. MBGCCA operates in two stages: (1) multimodal information integration, where TNF and abundance profiles are fused via a deep neural network trained using a multi-view contrastive loss, and (2) self-supervised graph representation learning, which leverages assembly graph topology to refine contig embeddings. The contrastive learning objective follows the InfoMax principle by maximizing mutual information across augmented views and modalities, encouraging the model to extract globally consistent and high-information representations. By aligning perturbed graph views while preserving topological structure, MBGCCA effectively captures both global genomic characteristics and local contig relationships. Comprehensive evaluations using both synthetic and real-world datasets-including wastewater and soil microbiomes-demonstrate that MBGCCA consistently outperforms state-of-the-art binning methods, particularly in challenging scenarios marked by sparse data and high community complexity. These results highlight the value of entropy-aware, topology-preserving learning for advancing metagenomic genome reconstruction.

canonical correlation analysis↗
PubMedDate not supplied

Clinical patient management and the integrated health information system.

Emerging progress in clinical applications of patient care computing is identified. The essential clinical skill is understanding what data are appropriate in any given patient care situation and extracting enough information to make the correct management decision. The value of the computer has less to do with the internal intellectual process of diagnosis than its contribution to the more manifest actions in support of clinical patient management. Techniques with which the computer is assisting in improving the clinical decisionmaking process are reviewed, and a mechanism to link them to active patient care settings is described. In addition, a trend toward the integration of various independent subsystems, so that expensive resources can be optimized for patient needs, is noted.

Computers↗
PubMed1979

An attempted integration of information relevant to schizophrenic subtypes.

The usefulness and validity of traditional subtypes are questionable. The subtypes described in earlier years no longer emerge with the clarity previously described. The four classical subtypes cannot be reliably distinguished and have not been shown to have predictive validity. Subtypes classified along course or prognostic lines may be more clinically useful. Attempts to subdivide schizophrenia along biologic and genetic lines offer promise. Recent efforts to describe new subdivisions of schizophrenia are readily justified, but new descriptive subtypes are likely to prove useful only when validated by biological, genetic, treatment response, and outcome data.

Adult↗
PubMed1978

Comment on internal feedback as a theory of judgment: a reply to Levin.

Levin's suggestion that internal feedback strategies be employed in judgmental and learning tasks is discussed. The predictions of an internal feedback notion are seen as inconsistent with Veit's ratio and difference task data. Scale-free frameworks and scale-convergence criteria used in previous research are described as useful techniques for separating integration from judgmental processes in information-integration as well as learning-task situations.

Feedback↗
PubMed1978

Testing toxic substances for protection of the environment.

The Toxic Substances Control Act requires pre-production testing of chemicals for potential hazards to human and environmental health. Effective control of chemicals requires evaluations of chemical hazard that go beyond determinations of toxicity to humans to include the effects, transport, and fat of chemicals in the environemnt. Formulation of meaningful hazard evaluations depends on integrating information from tests of chemical effects, transport, and fate or by developing testing tools that integrate these factors during experimentation. Chemical effects may be acute or chronic and they may be observed individual organisms, populations or organisms, or in total ecosystems. Chemical transport through the environment depends on physico-chemical characteristics of the chemical and the medium (soil, water, or air) as well as environmental factors and biotic processes. The ultimate fate of chemicals (persistence, transformation, or degradation) is determined by numerous physical and biological processes occurring in the environment, and must be acknowledged to effectively determine the hazard. Many techniques are available for the separate and routine evaluation of the effects, transport and fate of environmental contaminants. However, separate identification of the importance and magnitude of each of these factors limits their utility in assessments of chemical hazard. The microcosm (model ecosystem) method integrates many of these tests in replicable experimental units, and may provide substantial information on chemical hazard in ecosystem context.

Chemical Phenomena↗
PubMed2026

Using the DNA language model, GROVER, to parse effects of sequence, chromatin and regulatory features on genome stability.

MOTIVATION: Genome stability is shaped by DNA sequence and chromatin context, but their relative contributions to double-strand break (DSB) sensitivity remain unclear. RESULTS: We show that the DNA language model, GROVER, can infer DSB location based on sequence. DSB hotspots tend to contain GC-rich sequences that belong to promoters, genes and short interspersed nuclear elements (SINEs). Additionally, we identified several specific short sequences (tokens) that are associated with modulating DSB sensitivity. Another model using chromatin and genome regulatory features outperforms the sequence-only model, highlighting complementary and cell-type specific information. Integrating sequence and genome biological features yields the best performance, demonstrating their synergy. Analyzing this model revealed that, dependent on the sample, genome stability information encoded in H3K36me3 and DNase-seq can be learned from the sequence, but not H3K27ac or H3K9me3. Embedding chromatin data directly into the GROVER architecture enabled cell-type specific modeling with performance matching the full chromatin feature model. Our results suggest that while chromatin and regulatory context provides important information, such as cell-type specificity, much of the information shaping DSB patterns is already encoded in the DNA sequence itself. Our integrative modeling approach not only reveals DSB patterns but also provides a generalizable strategy for tracing predictions in genomic data. AVAILABILITY: Data, models, and a tutorial are available on Zenodo.

Chromatin↗