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PubMed1992

Characteristics of fragile X relatives with different attitudes toward terminating an affected pregnancy.

Female relatives of individuals with fragile X syndrome were asked whether they would terminate an affected pregnancy. Women were grouped according to how they answered this question and compared according to demographic characteristics, knowledge about the syndrome, perception of their risk for having an affected child, factors they considered important in family-planning decisions, and the magnitude of individual problems they perceived to be associated with raising an affected child. Important differences were identified between women willing to consider abortion and those who would not abort and between women who indicated what they would do and those who were unsure.

Abortion, Eugenic↗
PubMed1994

Rapid diagnostic tests in microbiology in the 1990s.

The selection and management of all diagnostic tools should be guided in the 1990s by carefully informed decisions. Concerns of test sensitivity and specificity must be balanced against cost. Although clinical judgment alone is often prompt and cost-effective, the risk of inaccuracy and serious consequences may be too great to forgo rapid diagnostic assays. The clinical effect and the imperatives in health care of the 1990s will guide the intelligent management and use of advancing rapid assay technology.

Chlamydia trachomatis↗
PubMed1994

Cognitive performance in learning disabled children with and without epilepsy.

Cognitive functioning and educational achievement were examined in learning disabled children with epilepsy (n = 65) and without epilepsy (n = 122) in order to explore whether children with epilepsy show unique types of learning problems, different from those in other learning disabled children. The learning disabled children with epilepsy tended to perform better on tests of verbal intelligence, certain achievement-related abilities and were better in one area of academic achievement, i.e. spelling. Despite their superior performance in these areas, the learning disabled children with epilepsy were slower than those without epilepsy and regular education controls (n = 100) on simple auditory and visual reaction tasks as well as on a multiple decision reaction task and a visual searching task. The results obtained with the school achievement tasks provide no clear evidence for specific types of learning impairment in children with epilepsy. Learning disabled children with epilepsy do not appear to have educational needs different from those of other learning disabled children.

Attention↗
PubMed1988

Problem behavior and psychiatric impairment within a developmentally disabled population. III: Psychotropic medication.

This report is the third in a series on problem behavior and psychiatric impairment in a population of 35,000 individuals receiving developmental disabilities services. Young and middle-aged adults were found to receive psychotropic medication at higher rates than children, adolescents, or elderly persons. Psychotropic receipt rates were found to increase with increasing severity of mental retardation, but most evidently with increasing restrictiveness of residential setting, increasing rated severity of problem behaviors, and presence of a psychiatric impairment. Rates of medication receipt also varied as a function of psychiatric diagnostic category. Discussion remarks emphasize the need to include information relative to clinical and social aspects of program settings and the roles and decision-making performance of physicians and psychologists in research on settings serving persons with developmental disabilities.

Adolescent↗
PubMed1993

Client/server power attracts healthcare markets.

Client/server architecture has become the darling of I/S professionals. The intelligence is spread among several processors, creating enormous flexibility. But are C/S systems easier, cheaper and faster than the good old mainframe? Not quite yet.

Computer Communication Networks↗
PubMed1980

[Studies of incest].

Theories of the genesis of incest tabus are presented and possible causes of a high degree of latent incest criminality are discussed. On the basis of the evaluation of 32 forensic-psychiatric expertises, characteristics of the committers and criminogenic conditions of the delict are discussed. The author arrives at the opinion that there is no determined type of incestuous delinquents. Decisive causes of later incest criminality will certainly be found in insufficiently introjected value norms within emotionally disturbed parental families and in the mainly primarily disturbed families of the delinquent.

Adolescent↗
PubMedDate not supplied

Can patients drive the future of health care?

As the traditional system of health care in the United States gives way to a regime run increasingly by the private sector, a powerful force is emerging: the patient. According to Harvard Business School professor Regina Herzlinger, health care is much like other service industries. Providers that hope to survive must cater to increasingly demanding and well-educated consumers. In a review of Herzlinger's book Market-Driven Health Care: Who Wins, Who Loses in the Transformation of America's Largest Service Industry, Alexandra Wyke, managing editor at the Economist Intelligence Unit, argues that the path to consumerism in medicine will be longer and bumpier than Herzlinger suggests. Consumers of medicine don't simply want health care to be more convenient; they want cures for all ills. How can providers gratify this appetite for ever better medicine? Furthermore, patients are not always capable of making sound decisions about their medical care. And health care professionals, who emphasize the complex nature of decision making in medicine, are doing their best to keep patients from holding the health care steering wheel. Herzlinger has written a bullish book on the virtues of market-driven health care, but, Wyke contends, she has overlooked the far-reaching effects that emerging technology could have in shaping medicine--especially in reducing the need for specialists. She also has given short shrift to the young managed-care industry, which has succeeded in controlling costs and is now under competitive pressure to meet patients' needs better.

Acquired Immunodeficiency Syndrome↗
PubMed1990

Semi-quantitative simulation for reasoning about physiological models of drug kinetics and effects.

Inter- and intra-individual pharmacokinetic or pharmacodynamic variability is a major cause of adverse drug reactions or ineffective therapy. We are developing a computer-based tool for predicting the consequences of different physiological and pathological states and for reasoning about the possible causes of observed variability that may be useful both in a clinical decision support environment for drug monitoring and as a research aid in the investigation of the influence of physiological factors on drug response. It is based on a physiological approach to pharmacokinetic modeling in which actual anatomical or physiological entities, such as organs, tissues or blood flows, are represented. These models serve as the basis for semi-quantitative simulation, a method linking classical quantitative simulation (by numerical integration of differential equations) with artificial intelligence-based qualitative simulation techniques. This approach retains the mathematical power of the Systems Dynamics method for solving complex, time-varying systems containing feed-back loops, which are intractable for current qualitative knowledge representation techniques, and extends it with the causal reasoning and explanation power of symbolic inference techniques used in expert systems. It also allows problem solving in situations, so common in medicine, where initial values of variables and parameters cannot be estimated precisely. Simulation outputs are intended to be qualitatively, but not necessarily quantitatively, correct. The semi-quantitative simulation method was originally developed in MacLisp on a DEC 2060 and applied to modeling cardio-vascular physiology. We are porting the code to Common Lisp on a Macintosh and adapting the approach to pharmacology, concentrating on drug metabolism issues, with lidocaine pharmacokinetics as a test case.

Computer Simulation↗
PubMed1988

Comparison of different models of diabetes care on compliance with self-monitoring of blood glucose by memory glucometer.

The modern management of diabetes relies heavily on self-monitoring of blood glucose (SMBG), and therefore SMBG records are an important source of clinical data for management decision making. The development of a memory Glucometer has provided the opportunity to verify the validity of glucose records thus generated and observe the effects of different educational approaches on compliance with SMBG. Thirty-four patients without previous experience of SMBG were randomized into one of the following experimental groups differing in the model of diabetes care: mutual decision making, didactic, and authoritarian. Patients, unaware of the memory capacity of the glucose meter, were required to perform four glucose measurements per day over a 14-day observation period. Patient-generated blood glucose records were then compared with objective records stored in the glucose-meter memory. Patients with gestational diabetes mellitus recorded a lower proportion of correct results (63 vs. 79%, P = .049) and exhibited a tendency to invent results with lower blood glucose levels (5.3 vs. 7.5 mM, P less than .0001) than the results omitted compared with patients with non-insulin-dependent diabetes mellitus. Predictors of greater validity of records were perceived intelligence of the subject (chi 2 = 4.56, P less than .02) and private health-insurance status (chi 2 = 4.52, P less than .04), whereas the experimental group assignment was not significant. These findings reflect potential motivational and sociodemographic limitations in the validity of SMBG recordings within the management and education of patients with gestational and nongestational diabetes.

Blood Glucose Self-Monitoring↗
PubMed2000

A new dose model for assessment of health risk due to contaminants in air.

The problem of making quantitative assessments of the risks associated with human exposure to toxic contaminants in the environment is a pressing one. This study demonstrates the capability of a new computational technique involving the use of fuzzy logic and neural networks to produce realistic risk assessments. The systematic analysis of human exposure involves the use of measurements and models, the results of which are sometimes used in regulatory decisions or in the drafting of legislation. Because of limited scientific understanding, however, interpretation of models often involves substantial uncertainty. Extensive measurement programs can be very expensive. The high complexity and inherent heterogeneity of exposure analysis is still a major challenge. The approach to this challenge tested here is to use a new model incorporating sophisticated artificial intelligence algorithms. Exposure assessment often requires that a number of factors be evaluated, including exposure concentrations, intake rates, exposure times, and frequencies. These factors are incorporated into a system that can "learn" the relevant relationships based on a known data set. The results can then be applied to new data sets and thus be applied widely without the need for extensive measurements. In this analysis, an example is developed for human health risk through inhalation exposure to benzene from vehicular emissions in the cities of Auckland and Christchurch, New Zealand. Risk factors considered were inhaled contaminant concentration, age, body weight, and activity patterns of humans. Three major variables affecting the inhaled contaminant concentration were emissions (mainly from motor vehicles), meteorology (wind speed, temperature, and atmospheric stability), and site factors (hilly, flat, etc.). The results are preliminary and used principally to demonstrate the technique, but they are very encouraging.

Age Factors↗
PubMed1994

Automatic processing in mildly retarded and nonretarded persons.

Mildly retarded adults, equal mental age nonretarded children, high mental age nonretarded children, equal chronological age nonretarded adults and young nonretarded adults were required to perform a priming task (letters/digits) in which some primes were masked (visual noise mask) at just below detection levels to assess automatic processing. The critical (just below detection level) prime-mask stimulus onset asynchronies (SOAs) were established individually for each subject using the method of limits and reassessed after the experimental trials. The mean critical SOA for each of the five groups was comparable and the critical SOAs remained stable across the 120 experimental trials for all groups. The nonretarded adult subjects demonstrated semantic, categorical and orthographic priming. The mildly retarded, the equal-MA and the high-MA groups failed to demonstrate priming, and in fact, demonstrated superior performance for prime-target conditions which should have been poorest. This finding was discussed in terms of the level of specificity engendered in the priming task. Under the mask procedure, the nonretarded adult groups demonstrated semantic (letter) priming and orthographic priming, suggesting that letters (not digits) function as an analog to words which were employed in earlier masked prime lexical decision tasks. The mentally retarded, the equal-MA and the high-MA groups again failed to demonstrate priming under the mask procedure.

Adolescent↗
PubMed2006

Assessing performance of prediction rules in machine learning.

INTRODUCTION: An important goal in machine learning is to assess the degree to which prediction rules are robust and replicable, since these rules are used for decision making and for planning follow-up studies. This requires an estimate of a prediction rule's true error rate, a statistic that can be estimated by resampling data. However, there are many possible approaches depending upon whether we draw observations with or without replacement, or sample once, repeatedly, or not at all, and the pros and cons of each are often unclear. This study illustrates and compares different methods for estimating true error with the aim of providing practical guidance to users of machine learning techniques. METHODS: We conducted Monte Carlo simulation studies using four different error estimators: bootstrap, split sample, resubstitution and a direct estimate of true error. Here, 'split sample' refers to a single random partition of the data into a pair of training and test samples, a popular scheme. We used stochastic gradient boosting as a learning algorithm, and considered data from two studies for which the underlying data mechanism was known to be complex: a library of 6000 tripeptide substrates collected for analysis of proteasome inhibition as part of anticancer drug design, and a cardiovascular study involving 600 subjects receiving antiplatelet treatment for acute coronary syndrome. RESULTS: There were important differences in the performance of the various error estimators examined. Error estimators for split sample and resubstitution, while being the most transparent in action and the simplest to apply, did not quantify the performance of prediction rules as accurately as the bootstrap. This was true for both types of study data, despite their highly different nature. CONCLUSIONS: The robustness and reliability of decisions based on analysis of genomics data could, in many cases, be improved by following best practices for prediction error estimation. For this, techniques such as bootstrap should be considered.

Algorithms↗
PubMed1993

Digital signal processing (DSP) applications for multiband loudness correction digital hearing aids and cochlear implants.

Single-chip digital signal processors (DSPs) allow the flexible implementation of a large variety of speech analysis, synthesis, and processing algorithms for the hearing impaired. A series of experiments was carried out to optimize parameters of the adaptive beamformer noise reduction algorithm and to evaluate its performance in realistic environments with normal-hearing and hearing-impaired subjects. An experimental DSP system has been used to implement a multiband loudness correction (MLC) algorithm for a digital hearing aid. Speech tests in quiet and noise with 13 users of conventional hearing aids demonstrated significant improvements in discrimination scores with the MLC algorithm. Various speech coding strategies for cochlear implants were implemented in real time on a DSP laboratory speech processor. Improved speech discrimination performance was achieved with high-rate stimulation. Hybrid strategies incorporating speech feature detectors and complex decision algorithms are currently being investigated.

Adult↗
PubMed2002

Automated fault-management in a simulated spaceflight micro-world.

BACKGROUND: As human spaceflight missions extend in duration and distance from Earth, a self-sufficient crew will bear far greater onboard responsibility and authority for mission success. This will increase the need for automated fault management (FM). Human factors issues in the use of such systems include maintenance of cognitive skill, situational awareness (SA), trust in automation, and workload. This study examine the human performance consequences of operator use of intelligent FM support in interaction with an autonomous, space-related, atmospheric control system. METHODS: An expert system representing a model-base reasoning agent supported operators at a low level of automation (LOA) by a computerized fault finding guide, at a medium LOA by an automated diagnosis and recovery advisory, and at a high LOA by automate diagnosis and recovery implementation, subject to operator approval or veto. Ten percent of the experimental trials involved complete failure of FM support. RESULTS: Benefits of automation were reflected in more accurate diagnoses, shorter fault identification time, and reduced subjective operator workload. Unexpectedly, fault identification times deteriorated more at the medium than at the high LOA during automation failure. Analyses of information sampling behavior showed that offloading operators from recovery implementation during reliable automation enabled operators at high LOA to engage in fault assessment activities CONCLUSIONS: The potential threat to SA imposed by high-level automation, in which decision advisories are automatically generated, need not inevitably be counteracted by choosing a lower LOA. Instead, freeing operator cognitive resources by automatic implementation of recover plans at a higher LOA can promote better fault comprehension, so long as the automation interface is designed to support efficient information sampling.

Adult↗
PubMed2006

Fuzzy support vector machines for adaptive Morse code recognition.

Morse code is now being harnessed for use in rehabilitation applications of augmentative-alternative communication and assistive technology, facilitating mobility, environmental control and adapted worksite access. In this paper, Morse code is selected as a communication adaptive device for persons who suffer from muscle atrophy, cerebral palsy or other severe handicaps. A stable typing rate is strictly required for Morse code to be effective as a communication tool. Therefore, an adaptive automatic recognition method with a high recognition rate is needed. The proposed system uses both fuzzy support vector machines and the variable-degree variable-step-size least-mean-square algorithm to achieve these objectives. We apply fuzzy memberships to each point, and provide different contributions to the decision learning function for support vector machines. Statistical analyses demonstrated that the proposed method elicited a higher recognition rate than other algorithms in the literature.

Algorithms↗
PubMed2004

Categorical versus dimensional approaches to diagnosis: methodological challenges.

The arguments pitting categorical versus dimensional approaches to psychiatric diagnosis have been long ongoing with little sign of imminent resolution. We argue that categorical and dimensional approaches are fundamentally equivalent, but that one or other approach is more appropriate depending on the clinical circumstances and research questions being addressed. This paper aims to demonstrate (a) how these two approaches necessarily interdigitate, (b) to clarify the conditions under which one should utilize one approach over the other, and (c) to alert psychiatric clinicians and researchers to issues in the methodology literature that might facilitate their considerations. Using an example from the Infant Health and Development Program (IHDP), we illustrate the importance of using dimensional approaches for hypothesis testing, identify the problems with power and with interpretation that arise from employing a categorical approach, and underscore the importance of identifying the appropriate cutpoints when a categorical approach is necessitated. We argue that failure to utilize the correct approach under the appropriate circumstances can result in impaired clinical and research decision-making.

Adult↗
PubMed2003

Integrating GIS components with knowledge discovery technology for environmental health decision support.

This paper presents a new category of decision-support tools that builds on today's Geographic Information Systems (GIS) and On-Line Analytical Processing (OLAP) technologies to facilitate Geographic Knowledge Discovery (GKD). This new category, named Spatial OLAP (SOLAP), has been an R&D topic for about 5 years in a few university labs and is now being implemented by early adopters in different fields, including public health where it provides numerous advantages. In this paper, we present an example of a SOLAP application in the field of environmental health: the ICEM-SE project. After having presented this example, we describe the design of this system and explain how it provides fast and easy access to the detailed and aggregated data that are needed for GKD and decision-making in public health. The SOLAP concept is also described and a comparison is made with traditional GIS applications.

Artificial Intelligence↗
PubMed2004

Fast k-nearest neighbor classification using cluster-based trees.

Most fast k-nearest neighbor (k-NN) algorithms exploit metric properties of distance measures for reducing computation cost and a few can work effectively on both metric and nonmetric measures. We propose a cluster-based tree algorithm to accelerate k-NN classification without any presuppositions about the metric form and properties of a dissimilarity measure. A mechanism of early decision making and minimal side-operations for choosing searching paths largely contribute to the efficiency of the algorithm. The algorithm is evaluated through extensive experiments over standard NIST and MNIST databases.

Algorithms↗