SEARCH · PubMed Health
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.
Artificial intelligence, long a topic of basic computer science research, is now being applied to problems of scientific, technical, and commercial interest. Some consultation programs, although limited in versatility, have achieved levels of performance rivaling those of human experts. A collateral benefit of this work is the systematization of previously unformalized knowledge in areas such as medical diagnosis and geology.
The paper outlines a concept of the automatic medical examination system (MES) designed to aid a physician during his/her medical professional orientation. The authors propose a general MES schedule, define the term "professional inability" (in the medical sense). They provide evidence for that it is necessary to use the assessments made experts as to the professional disability of adolescents and young people who have chronic diseases and dysfunctions. The common principles in the construction of expert MES matrices are outlined. After its completion, MES may be used for purposes of medical professional orientation.
Dealing daily with various machines and various control specimens provides a lot of data that cannot be processed manually. In order to help decision-making we wrote specific software coping with the traditional QC, with patient data (mean of normals, delta check) and with criteria related to the analytical equipment (flags and alarms). Four machines (3 Ektachem 700 and 1 Hitachi 911) analysing 25 common chemical tests are controlled. Every day, three different control specimens and one more once a week (regional survey) are run on the various pieces of equipment. The data are collected on a 486 microcomputer connected to the central computer. For every parameter the standard deviation is compared with the published acceptable limits and the Westgard's rules are computed. The mean of normals is continuously monitored. The final decision induces either an alarm sound and the print-out of the cause of rejection or, if no alarms happen, the daily print-out of recorded data, with or without the Levey Jennings graphs.
The application of artificial intelligence techniques to real-world problems has produced promising research results, but seldom has a system become a useful tool in its domain of expertise. Notable exceptions are the DENDRAL (1) and MOLGEN (2) systems. This paper describes PUFF, a program that interprets lung function test data and has become a working tool in the pulmonary physiology lab of a large hospital. Elements of the problem that paved the way for its success are examined, as are significant limitations of the solution that warrant further study.
The current limited success of computer-assisted analysis of left ventricular (LV) dynamics is due to three main reasons: there is a strong tendency to remain within the realm of mathematical modeling for LV dynamics, and it is not at all clear that this is an adequate approach; in places where mathematical models alone may be insufficient, current computer science research into more sophisticated schemes is not yet complete, and thus, more basic research is required, particularly into artificial intelligence, representations of knowledge, and interpretation control structures, before applications such as LV performance can be solved, a view also stated in M. Boehm and K. Hoehne (in "Digital Image Processing in Medicine" (K. Hoehne, Ed.), Springer-Verlag, New York/Berlin, 1981); there is a distinct lack of knowledge about LV dynamics, in conjunction with disagreements about what is important to model and what terminology is to be used. Although each of these issues is addressed, the first two issues are concentrated on. Furthermore, a language for the expression of definitions for terminology has been designed, and a system for LV dynamics interpretation has been implemented.
Pharmacological information has been organized and encoded in rules and frames for systematic retrieval. This includes: delineation, definition, and hierarchical subdivision of mechanisms responsible for drug interactions; division of pharmacological agents into a hierarchy of subclasses to allow for defining interacting drugs by classes as well as by specific agents; correlation of drug classes and specific drugs with mechanisms by which they may be involved in drug interactions. This information, accessible through a natural language-like and menu driven interface, allows clinicians to know what may happen when two drugs are used together, why, what can be done to alleviate detrimental interactions, and what related drugs may also be involved in similar interactions.
Explore the source record for details and available documents.
The usefulness of amperometric detection in pharmaceutical analyses was investigated for different groups of drugs. The UV response at 254 nm and that at the absorption maximum of the solute were compared with the electrochemical signal obtained. The minimum detectable concentration (nanograms on-column) of each substance is reported for the three different detection systems. This comparison was performed for 72 drugs (local anaesthetics, antipyretics, tricyclic antidepressants, sulphonamides, sex hormones, beta-adrenoceptor blocking agents, phenothiazines, alkaloids, diuretics and penicillins). The median limit of detection of the amperometric detector (see definition in the text) is 1.0 ng on-column and the median gain in sensitivity, compared with UV detection is 22.5.
Explore the source record for details and available documents.
This paper presents a digitized version of a thermodynamic sorption database, implemented as a relational database with MS Access. It is mineral-specific and can therefore be used for additive models of complex solid phases such as rocks or soils. An integrated user interface helps users to access selected mineral and sorption data, to extract internally consistent data sets for sorption modeling, and to export them in formats suitable for other modeling software. Data records comprise mineral properties, specific surface area values, surface binding sites' characteristics, sorption ligand information, and surface complexation reactions. An extensive bibliography is included, providing links not only to the above listed data, but also to background information concerning surface complexation model theories, evidence for surface species, and sorption experimental techniques.
Using a learning set of 28 sequences able to bind calcium (each sequence is 12 residues long), we have built two filters by learning on this set. The first filter uses a pattern-matching technique and the second one takes into account the environment of amino-acids. These two filters have been used to find new calcium-binding proteins in a data bank. The results are discussed.
Explore the source record for details and available documents.
The elucidation of chemical structures from 2D NMR data commonly utilizes a combination of COSY, HMQC/HSQC, and HMBC data. Generally COSY connectivities are assumed to mostly describe the separation of protons that are separated by 1 skeletal bond (3JHH), while HMBC connectivities represent protons separated from carbon atoms by 1 to 2 skeletal bonds (2JCH and 3JCH). Obviously COSY and HMBC connectivities of lengths greater than those described have been detected. Though experimental techniques have recently been described to aid in the identification of the nature of the couplings the detection of whether a coupling is 2-bond or greater still remains a challenge in most laboratories. In the StrucEluc software system the common lengths of the connectivities, 1-bond for COSY and 1- or 2-bond for HMBC, derived from 2D NMR data are set as the default. Therefore, in the presence of any extended connectivities contradictions can appear in the 2D NMR data. In this article, algorithmic methods for the detection and removal of contradictions in 2D NMR data that have been developed in support of StrucEluc are described. The methods are based on the analysis of molecular connectivity diagrams, MCDs. These methods have been implemented in the StrucEluc system and tested by solving 50 structural problems with 2D NMR spectral data containing contradictions. The presence of contradictions was detected by the algorithm in 90% of the cases, and the contradictions were automatically removed in approximately 50% of the problems. A method of "fuzzy" structure generation in the presence of contradictions has been suggested and successfully tested in this work. This work will demonstrate examples of the application of developed methods to a number of structural problems.
Prolog D is a program that formalizes, in a controllable and reproducible manner, an algorithm developed to predict distribution coefficients of ionizable compounds at a given pH and varying counterion concentrations. Its predictive power has been evaluated with experimental log D values measured under standard conditions of buffers and ionic strength. Calculations were performed with the three different options for the estimation of partition coefficients (log P) implemented in the program. Considering the diversity of test compounds as well as the present state of the art in log P and pKa predictions, Prolog D proved to be very efficient and can be used as a tool to provide lipophilicity data. Prediction patterns and correlations with the observed data are of almost equal quality for all options, permitting acceptable results for 80% of the data.
AIM: To examine the population impact and effectiveness of the Pro-Change smoking cessation course based on the Transtheoretical Model (TTM) compared to standard self-help smoking cessation literature. DESIGN: Randomized controlled trial. SETTING: Sixty-five West Midlands general practices. PARTICIPANTS: Randomly sampled patients recorded as smokers by their general practitioners received an invitation letter and 2471 current smokers agreed. INTERVENTIONS: Responders were randomized to one of four interventions. The control group received standard self-help literature. In the Manual intervention group, participants received the Pro-Change system, a self-help workbook and three questionnaires at 3-monthly intervals, which generated individually tailored feedback. In the Phone intervention group, participants received the Manual intervention plus three telephone calls. In the Nurse intervention group, participants received the Manual intervention plus three visits to the practice nurse. MEASUREMENTS: Biochemically confirmed point prevalence of being quit and 6-month sustained abstinence, 12 months after study commencement. FINDINGS: A total of 9.1% of registered current smokers participated, of whom 83.0% were not ready to quit. Less than half of participants returned questionnaires to generate second and third individualized feedback. Telephone calls reached 75% of those scheduled, but few participants visited the nurse. There were small differences between the three Pro-Change arms. The odds ratio (95% confidence intervals) for all Pro-Change arms combined versus the control arm were 1.50 (0.85-2.67) and 1.53 (0.76-3.10), for point prevalence and 6-month abstinence, respectively. This constitutes 2.1% of the TTM group versus 1.4% of the control group achieving confirmed 6-month sustained abstinence. CONCLUSIONS: There was no statistically significant benefit of the intervention apparent in this trial and the high relapse of quitters means that any population impact is small.
Explore the source record for details and available documents.
TRANSFAC is a database on transcription factors, their genomic binding sites and DNA-binding profiles. In addition to being updated and extended by new features, it has been complemented now by a series of additional database modules. Among them, modules which provide data about signal transduction pathways (TRANSPATH) or about cell types/organs/developmental stages (CYTOMER) are available as well as an updated version of the previously described COMPEL database. The databases are available on the WWW at http://transfac.gbf.de/