Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “decision intelligence”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

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

At least 937 records · Page 52Linked to original sources
PubMed1994

Improving prediction of preterm birth using a new classification scheme and rule induction.

Prediction of preterm birth is a poorly understood domain. The existing manual methods of assessment of preterm birth are 17%-38% accurate. The machine learning system LERS was used for three different datasets about pregnant women. Rules induced by LERS were used in conjunction with a classification scheme of LERS, based on "bucket brigade algorithm" of genetic algorithms and enhanced by partial matching. The resulting prediction of preterm birth in new, unseen cases is much more accurate (68%-90%).

Algorithms↗
PubMed1995

Curriculum of medical informatics and medical technology in the medical faculty.

1. CURRICULUM DESCRIPTION. Twenty years ago, our faculty organized several lessons in a physiology course to inform students about computers. Recently, new courses in informatics were established. In their first year, students take a compulsory course (15 hours=h) of basic computer science (computers databases, networking, and basic non-medical computer software). A special elective course in medical informatics (30h) can be taken in the 4th year (about 20% of students pass tis course). This course includes the following lessons: computers in medicine (2h), scientific information (4h), classification in medicine (2h- including ICD, SNOMED etc.), computer support of clinical decision (2h-calculation principles with demonstration), artificial intelligence (2h), statistical software (2h), hospital information systems (2h), software for practitioners (2h), biosignal and image analysis (4th), computers in pharmacology (2h), computer simulation (2h), support of metabolic care (2h-consultations, risk calculations), and laboratory information systems (2h). The same course, though slightly differences, is used for paramedical students (occupational therapy, health education, and nursing). Medical technology was established in a three year curriculum courses in the 1st year include common courses in electronic devices (60 h), computers and programming (120 h), biophysics (90 h), biomechanics (30 h), and different medical courses (500 h). For the 2nd and 3rd year, 75% of the courses (700 h per year) are technical e.g., medical devices, information systems, signal and picture analysis, laboratory technique, and data protection. 2. CONCLUSION AND PERSPECTIVES. Students of medicine, and some paramedical studies, are able to use computer in their profession after having taken these courses. Bachelors of medical technology find application in biomedical research, hospitals, and medical technology firms.

Curriculum↗
PubMed1995

Effective domain-dependent reuse in medical knowledge bases.

Knowledge reuse is now a critical issue for most developers of medical knowledge-based systems. As a rule, reuse is addressed from an ambitious, knowledge-engineering perspective that focuses on reusable general purpose knowledge modules, concepts, and methods. However, such a general goal fails to take into account the specific aspects of medical practice. From the point of view of the knowledge engineer, whose goal is to capture the specific features and intricacies of a given domain, this approach addresses the wrong level of generality. In this paper, we adopt a more pragmatic viewpoint, introducing the less ambitious goal of "domain-dependent limited reuse" and suggesting effective means of achieving it in practice. In a knowledge representation framework combining objects and production rules, we propose three mechanisms emerging from the combination of object-oriented programming and rule-based programming. We show these mechanisms contribute to achieve limited reuse and to introduce useful limited variations in medical expertise.

Artificial Intelligence↗
PubMedDate not supplied

Computational tools for the modern andrologist.

With such a wide array of computational tools to solve inference problems, andrologists and their mathematical or statistical collaborators face perhaps bewildering choices. It is tempting to criticize a method with which one is unfamiliar for its apparent complexity. Yet, many methods are quite elegant; neural computation uses nature's own best biological classifier, for example, and genetic algorithms apply rules of natural selection. Computer scientists will likely find no one single best inference engine to solve all classification problems. Rather, the modeler should choose the most appropriate computational tool based on the specific nature of a problem. If the problem can be separated into obvious components, a Markov chain may be useful. If the andrologist would like to encode a well-known clinical algorithm into the computer, the programmer may use an expert system. Once a modeler builds an inference engine, that engine is not truly useful until other andrologists use it to make inferences with their own data. Because a wide variety of computer hardware and software exists, it is a significant endeavor to translate, or "port," software designed and built on one machine to many other different computers. Fortunately, the World Wide Web offers a means by which computational tools may be made directly available to multiple users on many different systems, or "platforms." The World Wide Web refers to a standardization of information traffic on the global computer network, the Internet. The Internet is simply the linkage of many computers worldwide by computer operators who have chosen to allow other users access to their systems. Because many different types of computers exist, until recently only communication in very rudimentary form, such as text, or between select compatible machines, was available. Within the last half-decade, computer scientists and operators began to use standard means of communication between computers. Interpreters of these standard languages, such as Mosaic and Netscape, are now widely available, and they allow the casual user to access the most sophisticated multimedia aspects of computer information on a variety of different systems. Andrologists may thus use the World Wide Web to make inference engines that they have programmed available to other clinicians and researchers. For example, we programmed a World Wide Web interface to the neural networks that we trained in order to solve a number of andrology classification problems. Interested users connect to our address (at this writing http:@godot.urol.uic.edu), and they may fill out electronic forms with their own patient data, press a "predict" button, and nearly immediately view the results of our neural networks' prediction on their own computers. With the explosion in computer hardware technology, mathematics and computer science that once seemed esoteric can now be investigated on computers available to nearly all andrologists. Rapid advances in computer network technology now render a tool developed by one andrologist immediately available to many. Clearly, andrologists may expect that computational investigations in their field will be a productive ground in the near and far future.

Algorithms↗
PubMed1998

Timing is everything. Time-oriented clinical information systems.

Time is important in clinical information systems. Representing, maintaining, querying, and reasoning about time-oriented clinical data is a major theoretical and practical research area in medical informatics. In this nonexhaustive overview, we present a brief synopsis of research efforts in designing and developing time-oriented information systems in medicine. These efforts can be viewed from either an application point of view, distinguishing between different clinical tasks (such as diagnosis versus therapy) and clinical areas (such as infectious diseases versus oncology), or a methodological point of view, distinguishing between different theoretical approaches. We also explore the two primary methodological and theoretical paths research has taken in the past decade: temporal reasoning and temporal data maintenance. Both of these research areas include efforts to model time, temporal entities, and temporal queries. Collaboration between the two areas is possible, through tasks such as the abstraction of raw time-oriented clinical data into higher-level meaningful clinical concepts and the management of different levels of temporal granularity. Such collaboration could provide a common ground and useful areas for future research and development. We conclude with our view of future research directions.

Artificial Intelligence↗
PubMedDate not supplied

KBSIM/FLUIDTHERAPY: a system for optimized design of fluid resuscitation in trauma.

An application of the KBSIM (Knowledge-Based SIMulation) system to the improved design of fluid resuscitation is described. The system integrates knowledge from three domains, viz. the pathophysiology of traumatized patients represented in a quantitative biodynamic model, the heuristics of fluid resuscitation of such patients as represented in 'production rules', and some 'metaknowledge' reflected in the design of a multi-window user interface. This technique of combining numerical simulation with symbolic reasoning has obvious advantages during the design process and in training, by giving the user a possibility to evaluate his measures by direct feedback from the system. This feature of the system to assist in evaluation of alternative resuscitation procedures should also be useful as a means for decision support.

Artificial Intelligence↗
PubMed1985

Developments toward clinical support systems. Beyond accounts receivable.

The role of computers in primary care is disappointing when contrasted with their ubiquity elsewhere. This article surveys unique applications that have made inroads toward successful adaptation of automation to the storage and retrieval of medical data and to clinical decision support. The author's DUCHESS system is described as an effort to overcome the impediments that have restricted application of informatics to ambulatory care.

Artificial Intelligence↗
PubMed2000

The role of job control as a moderator of emotional dissonance and emotional intelligence-outcome relationships.

Job control may be defined as the latitude to make decisions and the freedom to select the most appropriate skills to complete the task. Emotional dissonance may be defined as the conflict between expressed and experienced emotions. In this study, job control and self-efficacy were theorized to jointly affect emotional dissonance. Individuals with high self-efficacy were found to be more satisfied under conditions of little job control, whereas those with low self-efficacy favored high job control. The impact of job control on emotional intelligence was also studied. Emotional intelligence may be defined as the set of skills that contribute to accurate self-appraisal of emotion as well as the detection of emotional cues in others and the use of feelings to motivate and achieve in one's life. Emotional intelligence and job control explained significant amounts of the variance in both job satisfaction and organizational commitment. Theoretical and practical implications are discussed.

Adult↗
PubMed2005

Genetically optimized fuzzy decision trees.

In this study, we are concerned with genetically optimized fuzzy decision trees (G-DTs). Decision trees are fundamental architectures of machine learning, pattern recognition, and system modeling. Starting with the generic decision tree with discrete or interval-valued attributes, we develop its fuzzy set-based generalization. In this generalized structure we admit the values of the attributes that are represented by some membership functions. Such fuzzy decision trees are constructed in the setting of genetic optimization. The underlying genetic algorithm optimizes the parameters of the fuzzy sets associated with the individual nodes where they play a role of fuzzy "switches" by distributing a flow of processing completed within the tree. We discuss various forms of the fitness function that help capture the essence of the problem at hand (that could be either of classification nature when dealing with discrete outputs or regression-like when handling a continuous output variable). We quantify a nature of the generalization of the tree by studying an optimally adjusted spreads of the membership functions located at the nodes of the decision tree. A series of experiments exploiting synthetic and machine learning data is used to illustrate the performance of the G-DTs.

Algorithms↗
PubMed1998

Fundamentals of clinical methodology: 2. Etiology.

The concept of etiology is analyzed and the possibilities and limitations of deterministic, probabilistic, and fuzzy etiology are explored. Different kinds of formal structures for the relation of causation are introduced which enable us to explicate the notion of cause on qualitative, comparative, and quantitative levels. The conceptual framework developed is an approach to a theory of causality that may be useful in etiologic research, in building nosological systems, and in differential diagnosis, therapeutic decision-making, and controlled clinical trials. The bearings of the theory are exemplified by examining the current Chlamydia pneumoniae hypothesis on the incidence of myocardial infarction.

Artificial Intelligence↗
PubMed2001

Application of artificial intelligence in audiology.

In this paper, machine learning methods based on artificial intelligence theory are applied to the computer-aided decision making of some otoneurological diseases, for example Ménière's disease. Three methods explored are decision trees, genetic algorithms and neural networks. By using such a machine learning method, the decision-making program is trained with a representative training set of cases and tested with another set. The machine learning methods are useful also for our otoneurological expert system, One, which is based on a pattern recognition approach. The methods are able to differentiate most of the cases tested between the six diseases included, provided that a sufficiently large training set is available.

Algorithms↗
PubMed2006

Differential performance on tasks of affective processing and decision-making in patients with Panic Disorder and Panic Disorder with comorbid Major Depressive Disorder.

BACKGROUND: Neuropsychological studies have provided evidence for deficits in psychiatric disorders, such as schizophrenia and mood disorders. However, neuropsychological function in Panic Disorder (PD) or PD with a comorbid diagnosis of Major Depressive Disorder (MDD) has not been comprehensively studied. The present study investigated neuropsychological functioning in patients with PD and PD + MDD by focusing on tasks that assess attention, psychomotor speed, executive function, decision-making, and affective processing. METHODS: Twenty-two unmedicated patients with PD, eleven of whom had a secondary diagnosis of MDD, were compared to twenty-two healthy controls, matched for gender, age, and intelligence on tasks of attention, memory, psychomotor speed, executive function, decision-making, and affective processing from the Cambridge Neuropsychological Test Automated Battery (CANTAB), Cambridge Gamble Task, and Affective Go/No-go Task. RESULTS: Relative to matched healthy controls, patients with PD + MDD displayed an attentional bias toward negatively-valenced verbal stimuli (Affective Go/No-go Task) and longer decision-making latencies (Cambridge Gamble Task). Furthermore, the PD + MDD group committed more errors on a task of memory and visual discrimination compared to their controls. In contrast, no group differences were found for PD patients relative to matched control subjects. LIMITATIONS: The sample size was limited, however, all patients were drug-free at the time of testing. CONCLUSIONS: The PD + MDD patients demonstrated deficits on a task involving visual discrimination and working memory, and an attentional bias towards negatively-valenced stimuli. In addition, patients with comorbid depression provided qualitatively different responses in the areas of affective and decision-making processes.

Adult↗
PubMed1987

A computational model of reasoning from the clinical literature.

This paper explores the premise that a formalized representation of empirical studies can play a central role in computer-based decision support. The specific motivations underlying this research include the following propositions: Reasoning from experimental evidence contained in the clinical literature is central to the decisions physicians make in patient care. A computational model, based upon a declarative representation for published reports of clinical studies, can drive a computer program that selectively tailors knowledge of the clinical literature as it is applied to a particular case. The development of such a computational model is an important first step toward filling a void in computer-based decision support systems. Furthermore, the model may help us better understand the general principles of reasoning from experimental evidence both in medicine and other domains. Roundsman is a developmental computer system which draws upon structured representations of the clinical literature in order to critique plans for the management of primary breast cancer. Roundsman is able to produce patient-specific analyses of breast cancer management options based on the 24 clinical studies currently encoded in its knowledge base. The Roundsman system is a first step in exploring how the computer can help to bring a critical analysis of the relevant literature to the physician, structured around a particular patient and treatment decision.

Artificial Intelligence↗
PubMed2005

Modeling of driver's collision avoidance maneuver based on controller switching model.

This paper presents a modeling strategy of human driving behavior based on the controller switching model focusing on the driver's collision avoidance maneuver. The driving data are collected by using the three-dimensional (3-D) driving simulator based on the CAVE Automatic Virtual Environment (CAVE), which provides stereoscopic immersive virtual environment. In our modeling, the control scenario of the human driver, that is, the mapping from the driver's sensory information to the operation of the driver such as acceleration, braking, and steering, is expressed by Piecewise Polynomial (PWP) model. Since the PWP model includes both continuous behaviors given by polynomials and discrete logical conditions, it can be regarded as a class of Hybrid Dynamical System (HDS). The identification problem for the PWP model is formulated as the Mixed Integer Linear Programming (MILP) by transforming the switching conditions into binary variables. From the obtained results, it is found that the driver appropriately switches the "control law" according to the sensory information. In addition, the driving characteristics of the beginner driver and the expert driver are compared and discussed. These results enable us to capture not only the physical meaning of the driving skill but the decision-making aspect (switching conditions) in the driver's collision avoidance maneuver as well.

Accidents, Traffic↗
PubMed2006

Developmental instability and the neural dynamics of the speed-intelligence relationship.

Two of the most securely established findings in the biology of intelligence are the relationship between reaction time (RT) and intelligence, and the heritability of intelligence. To investigate why RT may related to intelligence, researchers have used a variety of techniques to subdivide RT into cognitive and motor components. In the current study, magnetoencephalographic (MEG) dipole latencies were used to examine the speed and timing of specific brain processing stages engaged during visually cued simple and choice reaction time tasks. Simple and choice reaction time and timing of MEG sources were considered in relation to fluid intelligence (as measured by the Raven's Advanced Progressive Matrices, RAPM). To address heritability of intelligence, developmental instability (DI) was assessed, measured here as fluctuating asymmetry. DI represents the degree to which an organism is susceptible to developmental stress arising from both environmental and genomic sources. Analyses showed that choice, but not simple reaction time was negatively correlated with RAPM score. MEG revealed a set of complex relationships between the timing of regional brain activations and psychometric intelligence. The neural component associated with integration of sensory and motor information was most associated with RAPM compared to other components. Higher values of fluctuating asymmetry predicted reduced psychometric intelligence, a result suggesting that some part of the variance of the heritability of intelligence reflects DI. Fluctuating asymmetry was significantly and negatively correlated with timing during all components of task completion. These observations suggest that fluid intelligence is primarily related to speed during processing associated with decision time, while fluctuating asymmetry predicted slower processing across all stages of information processing.

Adolescent↗
PubMed1994

Is 20 years too long?: improving intelligibility in long-standing dysarthria--a single case treatment study.

Resource management decisions by most speech and language therapists would suggest that treatment for a dysarthric client of 20 years' duration should be a low priority. This study describes the therapy of a dystonic client who had been virtually speechless for 20 years because of his severe dysarthria. Assessment of his speech revealed that lip rounding was particularly difficult for him. He was offered eight sessions of general dysarthria therapy and eight sessions of therapy specifically designed to reduce lip tension. The hypotheses driving this therapy plan were that it would be possible to effect changes in his longstanding speech patterns and that therapy focused on reducing lip tension would be more effective than non-specific dysarthria therapy. An intelligibility test was designed to monitor any changes in his speech production. Therapy improved the client's intelligibility and increased his confidence and consequent functional use of speech.

Communication↗
PubMed1998

Modelling medical decisions in DynaMoL: a new general framework of dynamic decision analysis.

Dynamic decision analysis concerns decision problems in which both time and uncertainty are explicitly considered. We present a new dynamic decision analysis framework, called DynamoL, that supports graphical presentation of the decision factors in multiple perspectives. To alleviate the difficulty in assessing conditional probabilities over time in dynamic decision models, DynaMoL incorporates a Bayesian learning system to automatically learn the probabilistic parameters from large medical databases. We describe the DynaMoL modeling and learning architecture through a medical decision problem on the optimal follow-up schedule for patients after curative colorectal cancer surgery. We also show that the modeling experience and results indicate practical promise for the framework.

Artificial Intelligence↗