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PubMed2000

KIDSCARE: a network for children with special health care needs.

In December 1997, Arkansas Medicaid in cooperation with Title V and Children's Medical Services (CMS) implemented guidelines for the preauthorization of therapy services for Children with Special Health Care Needs (CSHCN). The University of Arkansas for Medical Sciences (UAMS) in partnership with Arkansas Medicaid (MCD), and Chidren's Medical Services (CMS) were given the charge of developing clinical practice guidelines for physical therapy (PT), occupational therapy (OT), and speech/language therapy (SLP) for this population based on primary diagnosis and age appropriateness. This process involved the implementation of a statewide, internet-based, clinical information support network. The objective of this article is to describe KIDSCARE, a clinical information support network, currently under development, for the determination of medical necessity and allocation of therapy services for CSHCN.

Academic Medical Centers↗
PubMed2026

Comparative Effectiveness of Exercise Interventions for Hamstring Injury Prevention in Football Players: A Systematic Review and Network Meta-analysis.

BACKGROUND: Hamstring strain injury is a leading time-loss injury in football, yet trials have evaluated diverse exercise-based prevention programs with limited direct head-to-head evidence. This systematic review and network meta-analysis aimed to compare the effectiveness of exercise-based interventions for preventing hamstring injuries in football players using exposure-adjusted incidence rate ratios. METHODS: We conducted a PRISMA-aligned systematic review and random-effects network meta-analysis of randomized controlled trials in football players comparing exercise-based interventions to prevent hamstring injuries. Searches covered PubMed, Cochrane Library, Embase and Web of Science from inception to January 5, 2026. Interventions were modeled as separate nodes (Nordic hamstring exercise [NHE], FIFA 11, FIFA 11 + , FIFA 11 + Kids, bounding exercise program [BEP], usual training). The primary effect measure was incidence rate ratio (IRR) versus usual training, with ranking by P-scores; exploratory subgroup analyses were conducted by sex-restricted male-only evidence and age group. RESULTS: Eleven randomized controlled trials involving 9,282 participants were included. The network was connected but largely star-shaped, with most evidence comparing active interventions against usual training and no direct active-active comparisons. FIFA 11 + showed the most consistent exposure-adjusted association with reduced hamstring injury incidence versus usual training (IRR = 0.55, 95% CI 0.31-0.98; P-score = 0.84). FIFA 11 + Kids showed a favorable but imprecise estimate, whereas NHE showed a modest non-significant reduction and FIFA 11 and BEP showed no clear benefit. Male-only findings were broadly consistent with the primary analysis. Age-stratified analyses suggested that the apparent hierarchy was not fully identical across age strata, but subgroup networks were sparse and exploratory. RoB 2 judged three studies as high risk and eight as having some concerns; no trial was judged as overall low risk. Between-study heterogeneity was substantial, and treatment rankings were, therefore, interpreted cautiously. CONCLUSIONS: In this IRR-based network meta-analysis, FIFA 11 + showed the most consistent exposure-adjusted association with reduced hamstring injury incidence compared with usual training. However, certainty across the primary comparisons ranged from low to very low because of clinical and methodological heterogeneity, sparse direct evidence for several nodes, reliance on indirect active-active comparisons, substantial between-study heterogeneity, and moderate-to-high risk of bias across the included studies. The treatment hierarchy should, therefore, be interpreted as a low-to-very-low-certainty, population-level summary rather than as a basis for firm recommendations. Further well-reported, age- and population-specific head-to-head trials with consistent exposure, injury-definition, adherence, and intervention-dose reporting are needed. Registration Systematic review registration PROSPERO (CRD420251243576).

FIFA 11 + ↗
PubMed1996

Radial Basis Function Network Configuration Using Mutual Information and the Orthogonal Least Squares Algorithm.

Input nodes of neural networks are usually predetermined by using a priori knowledge or selected by trial and error. For example, in pattern recognition applications the input nodes are usually the given pattern features and in system identification applications the past input and output data are often used as inputs to the network. Some of the input variables may be irrelevant to the task in hand and therefore may cause a deterioration in network performance. Some may be redundant and may increase the complexity of the network and consume expensive computation time. In the present study, the mutual information between the input variables and the output of the network is used to select a suboptimal set of input variables for the network. The variables are selected according to the information content relevant to the output. Variables which have a higher mutual information with the output and lower dependence on other selected variables are used as network inputs. The algorithms are derived based on heuristics and performance is assessed by using radial basis function (RBF) networks trained with the orthogonal least squares algorithm (OLS), which selects the hidden layer nodes of the network according to the error reduction ratios on the network output. Both real and simulated data sets are used to demonstrate the effectiveness of the new algorithms. Copyright 1996 Elsevier Science Ltd.

Journal Article↗
PubMed1996

An Investigation into the Improvement of Local Minima of the Hopfield Network.

The paper investigates the improvement of local minima of the Hopfield network. A local minima escape algorithm (LME algorithm), is proposed for improving local minima of small-scale networks. Experiments on travelling salesman problems (TSP) show that the LME algorithm is an efficient algorithm in improving the local minima, and the comparison with the simulated annealing algorithm (SA) shows that the LME algorithm can produce better results in less time. The paper then investigates the improvement of local minima of large-scale networks. By combining the LME algorithm with a network partitioning technique, a network partitioning algorithm (NPA) is proposed. Experiments on 51 and 101-city TSP problems show that the local minima of large-scale networks can be greatly improved by the NPA algorithm, however, the global minima are still difficult to achieve. Copyright 1996 Elsevier Science Ltd

Journal Article↗
PubMedDate not supplied

Data input module for Birth Defects Systems Manager.

The need for a computational bioinformatics infrastructure to manage the vast digital information from functional genomics and proteomics motivated us to develop Birth Defects Systems Manager (BDSM) as an open resource to facilitate analysis and discovery in developmental biology and developmental toxicity. This report describes the design, development and implementation of the data loading module of BDSM, referred to as LoadBDSM. It includes a shared data directory resource that can be granted various levels of security for different research groups or investigators to manage experimental datasets individually or in groups. LoadBDSM allows the upload of data and experiment details using controlled semantics for developmental exposure (toxicant, dosing scenario, intervention), biological sample (species, tissue, stage) and disease outcome (time, risk, phenotype). It adheres to existing controlled vocabulary plus rules of inference (ontologies) for experiment, data and metadata annotations. LoadBDSM extends the capabilities of BDSM to support the emergence of "embryo-formatics" defined here as the data, information and knowledge from genomic sciences applied to, or derived from, an embryological context. This includes, but is not limited to, delineating pathways and biological regulatory networks for specific chemicals or classes of developmental toxicants, developing novel biomarkers indicative of exposure and/or predictive of adverse effects, and integrating modern computing and information technology with data from molecular biology.

Abnormalities, Drug-Induced↗
PubMed2000

The life of form. Emergent patterns of morphological transformation.

The problem of biological form remains unresolved despite the known details of gene activities in embryonic development. Segmentation is discussed in connection with observed gene activities and the question of generic regularities across phyla. The sciences of complexity and nonlinear dynamics are considered as contexts for the exploration of constraints at both the level of genetic networks and morphogenesis. A new model of morphogenetic constraints coupled to dynamic attractors is proposed as an approach to the question--how to unite the contingencies of evolutionary genetic changes with the emergent regularities of organismic morphologies?

Animals↗
PubMed1997

Chaos in Neural Networks Composed of Coincidence Detector Neurons.

Chaotic behaviour is observed in neural network models composed of coincidence detector neurons. We use a continuous time and deterministic point process model with uniform synaptic strength and random delay, and apply periodical external inputs to a few neurons in the network. We show that the network dynamics becomes chaotic when the length of "chain firing" starting from an external input becomes practically infinite. Copyright 1997 Elsevier Science Ltd.

Journal Article↗
PubMed1999

Taking the lead from a model.

It is rare these days that theory leads experiment in the biological sciences, but it still happens. A recent study has experimentally confirmed the predictions of a model aimed at explaining how neural networks interact to produce the coordinated patterns of motor activity necessary for effective behavior.

Animals↗
PubMedDate not supplied

Organizational factors that influence information technology diffusion in academic health sciences centers.

OBJECTIVE: To identify the organizational factors which influence the diffusion of end user online literature searching, the computer-based patient record, and electronic mail systems in academic health sciences centers in the United States. DESIGN: A total of 1335 individuals working in informatics and library areas at 67 academic health sciences centers in the U.S. were surveyed. Multivariate techniques were used to evaluate the relationship between the set of six organizational factors and two measures of innovation diffusion. MEASUREMENTS: A Guttman-like scale was developed to measure infusion, or depth or sophistication, of each of the three innovations at each institution. Diffusion was measured by a question previously developed for another study. Six independent variables were measured via five formerly developed scales and one new one. RESULTS: The overall response rate was 41%. The set of organizational variables produced significant results in the diffusion of each of the three innovations, with individual variables influencing diffusion to varying degrees. The same set produced significant results in relation to infusion only for online searching. There was little or no correlation between infusion and diffusion for each innovation. CONCLUSION: Organizational attributes are important predictors for diffusion of information technology innovations. Individual variables differ in their effect on each innovation. The set of attributes seems less able to predict infusion. It is recommended that both infusion and diffusion be measured in future studies because there is little relation between them. It is further recommended that individuals charged with implementing information technology in the health sciences receive training in managing organizational issues.

Academic Medical Centers↗
PubMed1992

Using telemedicine to improve health care in distant areas.

Many users consider telemedicine a partial solution to problems of delivering health care to remote areas or areas underserved by clinicians. Current telemedical technology benefits from recent developments such as the decreased cost and improved quality of the coder-decoder (codec) equipment used in interactive digital video systems and the expansion of fiber-optic cable networks. The authors outline some pioneering telemedicine programs of the 1960s and 1970s and describe two recently activated systems in Texas. One network, serving the western two-fifths of the state, links faculty members from four campuses of Texas Tech University Health Sciences Center with almost 40 rural communities. The other connects the state hospital and three other facilities in Austin with four health care sites in the town of Giddings, 65 miles away. Besides serving patients, the systems provide continuing medical education and support to reduce the isolation of rural health care professionals. Primary goals include evaluation and certification of telemedical training and analysis of the cost feasibility of telemedical services.

Delivery of Health Care↗
PubMed2002

[A competitive fund of development to improve the quality of university education in Chile. Area of health care].

In 1997, the Chilean Government and the International Bank for Development convened on a strategy to improve Chilean university education. It was based on quality improvement, effectiveness, relevancy and innovation on university education programs. A US$ 245 millions fund was afforded, for a five years competitive grants program, among certain traditional Universities and Technical Education Institutes. The authors reviewed the projects that won the contests during the first three years in the health area, to determine their impact, demands supported, difficulties and assets. These projects obtained 13.6% of the assigned funds (a total of US$ 16.5 millions). Funds were requested mostly to build spaces, obtain equipment, laboratories and computational support. Funds were also requested to carry out methodological changes and teaching improvements. The importance of teaching health sciences in locations outside the Metropolitan area of Santiago, the modification of undergraduate medical curriculum and the development of post graduate networks are emphasized.

Chile↗
PubMed2004

Advances in modeling of biomolecular interactions.

Modeling of molecular interactions is increasingly used in life science research and biotechnology development. Examples are computer aided drug design, prediction of protein interactions with other molecules, and simulation of networks of biomolecules in a particular process in human body. This article reviews recent progress in the related fields and provides a brief overview on the methods used in molecular modeling of biological systems.

Computer Simulation↗
PubMed2004

[Already in the 21st century ... a new leadership in health sciences].

It is a fact to state that health care has never succeeded in covering such a wide series of sectors of the population in our country. The health care network created both by public as well as private efforts, and occasionally due to the collaboration by both fields, offers a framework of health care services which ensures there is a satisfactory coverage for the general population. It is difficult to provide a rebuttal to this statement; all one needs to do is recall what the status of our health care system was a few years ago. We have not achieved a perfect system. The development of our health care network has been produced by expansion. As we have come to believe that health is an unalienable right, we have to expand health care services to cover everyone. This effort leads to a second phase which brings to bear upon us new problems. One is the quality of health care services and the second is cost.

Delivery of Health Care↗
PubMed2005

The evolution of the atheromatous plaque: ultrastructural evidence.

Our understanding of endothelial physiology is overdue compared with other areas of study. For too many years the complex mysteries of this thin single-layered cellular lamina covering the whole of the vascular network, from the large conduction vessel to the smallest resistance and diffusion vessel, have been hidden by an organ-based science more focused on organ pathology than on ultrastructural physiopathology. We tried to follow chronologically the alteration stages of this system of membranes in relation to the development of the atherosclerotic plaque in human biopsy.

Aorta↗
PubMed2026

Brain network alterations underlying cue reactivity and craving in abstinent methamphetamine users: a systematic review of functional MRI findings.

BACKGROUND: Methamphetamine use disorder (MUD) is marked by intense craving and high relapse risk, often triggered by drug-related cues. Functional magnetic resonance imaging (fMRI) provides key insight into the neural basis of this cue reactivity, implicating large-scale brain networks for reward, motivation, and control. Yet, findings remain inconsistent across studies due to differences in task design, abstinence duration, and participant characteristics. OBJECTIVE: This systematic review synthesises evidence on how abstinence influences brain network alterations underlying cue reactivity and craving in methamphetamine users, integrating task-based and resting-state fMRI findings within leading neurobiological models of addiction. METHODS: A systematic search of PubMed, Scopus, Web of Science, and Ovid was conducted up to August 10, 2025, following PRISMA 2020 guidelines. Eligible fMRI studies examined cue reactivity or craving in abstinent methamphetamine users. Data were extracted on activation, connectivity, and brain-behaviour associations, and synthesised narratively. RESULTS: Task-based studies revealed heightened activation across reward, salience, and control networks during cue exposure, which diminished as parietal and executive control systems re-engaged with longer abstinence. Resting-state findings showed disrupted intrinsic connectivity among default mode, salience, and frontoparietal networks, reflecting persistent imbalances linked to craving and use severity. CONCLUSION: fMRI evidence shows that MUD is marked by network-level disruption linking reward, salience, and control systems. Task-based findings reveal strong cue reactivity in reward circuits, while resting-state data show persistent imbalance among default mode and control networks. With abstinence, partial restoration of network integrity emerges, highlighting both vulnerability and opportunities for targeted, recovery-based interventions.

Humans↗
PubMed1995

HPCC and the National Information Infrastructure: an overview.

The National Information Infrastructure (NII) or "information superhighway" is a high-priority federal initiative to combine communications networks, computers, databases, and consumer electronics to deliver information services to all U.S. citizens. The NII will be used to improve government and social services while cutting administrative costs. Operated by the private sector, the NII will rely on advanced technologies developed under the direction of the federal High Performance Computing and Communications (HPCC) Program. These include computing systems capable of performing trillions of operations (teraops) per second and networks capable of transmitting billions of bits (gigabits) per second. Among other activities, the HPCC Program supports the national supercomputer research centers, the federal portion of the Internet, and the development of interface software, such as Mosaic, that facilitates access to network information services. Health care has been identified as a critical demonstration area for HPCC technology and an important application area for the NII. As an HPCC participant, the National Library of Medicine (NLM) assists hospitals and medical centers to connect to the Internet through projects directed by the Regional Medical Libraries and through an Internet Connections Program cosponsored by the National Science Foundation. In addition to using the Internet to provide enhanced access to its own information services, NLM sponsors health-related applications of HPCC technology. Examples include the "Visible Human" project and recently awarded contracts for test-bed networks to share patient data and medical images, telemedicine projects to provide consultation and medical care to patients in rural areas, and advanced computer simulations of human anatomy for training in "virtual surgery."

Computer Communication Networks↗
PubMed2004

Networks of innovation or networks of opportunity? The making of the Spanish antibiotics industry.

The pharmaceutical industry is a typically research-intensive, first world-industry. This article seeks to explain why it has been so difficult for late industrialised nations to reproduce the networks of innovation on which the design and manufacturing of new drugs has historically based, and why alternative concepts are needed in order to understand the dynamics of science-based industries in emerging countries. The article analyses the development of the Spanish antibiotics industry, build after the World War II under the strong influence of the new international order and Spain's political framework, academic traditions and business groups. Focusing on the long-term relationships established between two Spanish companies (Antibióticos SA and Compañía Española de Penicilina y Antibióticos, CEPA), their American technological partners (Schenley and Merck), and their social and scientific environment, the article identifies networks of opportunity as the key institutional arrangement of this new industry in Spain. Opportunity (as opposed to innovation) networks are thus proposed to conceptualise the development of technologically complex industries in the European periphery.

Anti-Bacterial Agents↗
PubMed2003

Pattern identification and classification in gene expression data using an autoassociative neural network model.

The application of DNA microarray technology for analysis of gene expression creates enormous opportunities to accelerate the pace in understanding living systems and identification of target genes and pathways for drug development and therapeutic intervention. Parallel monitoring of the expression profiles of thousands of genes seems particularly promising for a deeper understanding of cancer biology and the identification of molecular signatures supporting the histological classification schemes of neoplastic specimens. However, the increasing volume of data generated by microarray experiments poses the challenge of developing equally efficient methods and analysis procedures to extract, interpret, and upgrade the information content of these databases. Herein, a computational procedure for pattern identification, feature extraction, and classification of gene expression data through the analysis of an autoassociative neural network model is described. The identified patterns and features contain critical information about gene-phenotype relationships observed during changes in cell physiology. They represent a rational and dimensionally reduced base for understanding the basic biology of the onset of diseases, defining targets of therapeutic intervention, and developing diagnostic tools for the identification and classification of pathological states. The proposed method has been tested on two different microarray datasets-Golub's analysis of acute human leukemia [Golub et al. (1999) Science 286:531-537], and the human colon adenocarcinoma study presented by Alon et al. [1999; Proc Natl Acad Sci USA 97:10101-10106]. The analysis of the neural network internal structure allows the identification of specific phenotype markers and the extraction of peculiar associations among genes and physiological states. At the same time, the neural network outputs provide assignment to multiple classes, such as different pathological conditions or tissue samples, for previously unseen instances.

Adenocarcinoma↗