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PubMed1993

The design and implementation of a ventilator-management advisor.

VentPlan is an implementation of the architecture developed by the qualitative-quantitative (QQ) research group for combining qualitative and quantitative computation in a ventilator-management advisor (VMA). VentPlan calculates recommended settings for four controls of a ventilator by evaluating the predicted effects of alternative ventilator settings. A belief network converts clinical diagnoses to distributions on physiologic parameters. A mathematical-modeling module applies a patient-specific mathematical model of cardiopulmonary physiology to predict the effects of alternative ventilator settings. A decision-theoretic plan evaluator ranks the predicted effects of alternative ventilator settings according to a multiattribute-value model that specifies physician preferences for ventilator treatments. Our architecture allows VentPlan to interpret quantitative observations in light of the clinical context (such as the clinical diagnosis). We report a retrospective study of the ventilator-setting changes encountered in postoperative patients in a surgical intensive-care unit (ICU). We conclude that the QQ architecture allows VentPlan to apply a patient-specific physiologic model to calculate ventilator settings that are optimal with respect to a decision-theoretic value model describing physician preferences for setting the ventilator.

Algorithms↗
PubMed2004

Criticism or praise? The impact of verbal versus text-only computer feedback on social presence, intrinsic motivation, and recall.

The Computers Are Social Actors (CASA) paradigm asserts that human computer users interact socially with computers, and has provided extensive evidence that this is the case. In this experiment (n = 134), participants received either praise or criticism from a computer. Independent variables were the direction feedback (praise or criticism), and voice channel (verbal or text-only). Dependent variables measured via a computer-based questionnaire were recall, perceived ability, intrinsic motivation, and perceptions of the computer as a social entity. Results demonstrate that participants had similar reactions to computers as predicted by interpersonal communication research with participants who received text-only criticism reporting higher levels of intrinsic motivation, perceived ability, and recall. Additionally, the computer was seen as more intelligent. Implications for theory and application are discussed.

Adolescent↗
PubMed2002

Machine psychology: autonomous behavior, perceptual categorization and conditioning in a brain-based device.

In studying brain activity during the behavior of living animals, it is not possible simultaneously to analyze all levels of control from molecular events to motor responses. To provide insights into how levels of control interact, we have carried out synthetic neural modeling using a brain-based real-world device. We describe here the design and performance of such a device, designated Darwin VII, which is guided by computer-simulated analogues of cortical and subcortical structures. All levels of Darwin VII's neural architecture can be examined simultaneously as the device behaves in a real environment. Analysis of its neural activity during perceptual categorization and conditioned behavior suggests neural mechanisms for invariant object recognition, experience-dependent perceptual categorization, first-order and second-order conditioning, and the effects of different learning rates on responses to appetitive and aversive events. While individual Darwin VII exemplars developed similar categorical responses that depended on exploration of the environment and sensorimotor adaptation, each showed highly individual patterns of changes in synaptic strengths. By allowing exhaustive analysis and manipulation of neuroanatomy and large-scale neural dynamics, such brain-based devices provide valuable heuristics for understanding cortical interactions. These devices also provide the groundwork for the development of intelligent machines that follow neurobiological rather than computational principles in their construction.

Animals↗
PubMed1989

Crisis of meaning and medical informatics education: a burden and/or a relief?

Starting with the quotation by Paul Ricoeur: Man needs love indeed; he needs justice still more; but most of all he needs meaning, this paper states that in this present situation medical education does not prepare students to deal with human needs, neither their own nor those of their patients. This is due to the almost exclusive devotion to hard sciences, contaminated by unscientific ideological drift, which tends to negate subjectivity and to suppress any significance of human destiny. Although medical informatics, by definition, eliminates meaning and knowledge, it can - if properly used as a complement and not as a competitor of human intelligence - help to renovate medical education, introduce true humanistic dimensions, and restore the element of human subjectivity.

Artificial Intelligence↗
PubMed1993

Metaphor graphics to support integrated decision making with respiratory data.

Support for data integration in the intensive care unit (ICU) often includes efforts to improve the display of data. An electronic version of a flowsheet (table of numbers) with optimal line graphs is by far the most common format in current ICU computer workstation technology, yet there is little evidence that this format provides particularly good support for human integration of data. The present work introduces a new form of graphic representation, one that is far more metaphoric, far more tailored to the intensive care unit than a line graph. This graphic system, called volume rectangles represents mechanical ventilator data in such a way that is easy to keep different types of variables conceptually separated, yet easy to see how they relate in a truly integrated way. Volume rectangles are one example of a general approach to display of data called the metaphor graphic approach, which is being evaluated in this and other contexts. Metaphor graphics are custom tailored visual displays designed to look like the real world situation from which the data is collected but not in a literal sense of 'look like'. Anecdotal observation suggests that such graphics are easy to learn, are remembered over long period, and are good decision support tools when the task is finding patterns in a mass of data.

Artificial Intelligence↗
PubMed1997

Decision support system to assist mechanical ventilation in the adult respiratory distress syndrome.

This paper presents a knowledge-based decision support system to assist mechanical ventilation in patients with the Adult Respiratory Distress Syndrome (DSSARDS). The knowledge base uses clinical algorithms developed from interviews and seminars with experts. The system contains 140 rules, applies backward chaining and was built on an IBM-PC compatible microcomputer. Clinical and physiological data and ventilator settings were used for suggestions of ventilatory support mode (VSMODE) and settings (MVSET) and for hemodynamic evaluation and therapy (HEMO). Success rates (s) and kappa coefficient (k) were used to measure agreement between DSSARDS and physicians at 4 decision steps related to: beginning of mechanical ventilation (FIRSTSET), VSMODE, MVSET and HEMO, DSSARDS prototype was evaluated in a development phase with 6 patients aged 48.6 +/- 15.9 years. Agreement results for 142 decision steps were: FIRSTSET k = 0.90, s = 0.93; VSMODE k = 0.76, s = 0.92; HEMO k = 0.58, s = 0.70, MVSET k = 0.86, s = 0.92 (p < 0.05 for all k). Improvements in the knowledge base were performed mainly in HEMO and VSMODE modules. The subsequent test phase studied 5 patients aged 54.8 +/- 11.0 years in a total of 900 decision steps. Results were: FIRSTSET k = 0.93, s = 0.95; VSMODE k = 0.93, s = 0.96; HEMO k = 0.97, s = 0.99, MVSET k = 0.96, s = 0.97 (p < 0.05 for all k). The results indicate significant agreement between DSSARDS and physicians for all decision steps. This suggests that DSSARDS may be used as a support for decision making and a training tool for mechanical ventilation in patients with the adult respiratory distress syndrome.

Adult↗
PubMedDate not supplied

Case-based tutoring from a medical knowledge base.

The past decade has seen the emergence of programs that make use of large knowledge bases to assist physicians in diagnosis within the general field of internal medicine. One such program, Internist-I, contains knowledge about over 600 diseases, covering a significant proportion of internal medicine. This paper describes the process of converting a subset of this knowledge base--in the area of cardiovascular diseases--into a probabilistic format, and the use of this resulting knowledge base to teach medical diagnostic knowledge. The system (called KBSimulator--for Knowledge-Based patient Simulator) generates simulated patient cases and uses these cases as a focal point from which to teach medical knowledge. This project demonstrates the feasibility of building an intelligent, flexible instructional system that uses a knowledge base constructed primarily for medical diagnosis.

Artificial Intelligence↗
PubMedDate not supplied

Kave: a tool for knowledge acquisition to support artificial ventilation.

A decision support system for artificial ventilation is being developed. One of the fundamental goals for this system is the application of the system when a domain expert is not present. Such a system requires a rich knowledge base. The knowledge acquisition process is often considered to be the bottleneck in acquiring such a complete knowledge base. Since no single available method, for example interviewing domain experts, is sufficient for removing this bottleneck, we have chosen a combination of different methods. The different backgrounds of knowledge engineers and domain experts could cause communication restrictions and difficulties between them, e.g. they might not understand each others knowledge domain and this will affect formulation of the knowledge. To solve this problem we needed a tool which supports both the knowledge engineer and the domain expert already from the initial phase of developing the knowledge base. We have developed a knowledge acquisition system called KAVE to elicit knowledge from domain experts and storing it in the knowledge base. KAVE is based on a domain specific conceptual model which is a result of cooperation between knowledge engineers and domain experts during identification, design and structuring of knowledge for this domain. KAVE includes a patient simulator to help validate knowledge in the knowledge base and a knowledge editor to facilitate refinement and maintenance of the knowledge base.

Artificial Intelligence↗
PubMed1993

Model-based diagnosis in intensive care monitoring: the YAQ approach.

YAQ is an ontology for model-based reasoning in physiologic domains. YAQ is based on a hybrid algebra of qualitative and numerical values, and is designed to benefit from the rich and ever-changing nature of information available in a critical care monitoring environment. The focus of the project is on diagnosis of clinical conditions, prediction of the effects of therapy, and therapy management assistance. Two models of diagnosis are implemented in YAQ: diagnosis based on associations, and model-based diagnosis. The ontology is applied to the domain of ventilator management in infants with respiratory distress syndrome (RDS). The article describes the diagnostic capabilities of YAQ, illustrates these concepts on examples taken from actual patient records, and reports the results of an evaluation of the diagnostic performance on the RDS/assisted ventilation domain model.

Artificial Intelligence↗
PubMedDate not supplied

Data, knowledge and method bases in chemical sciences. Part IV. Current status in databases.

Computer readable databases have become an integral part of chemical research right from planning data acquisition to interpretation of the information generated. The databases available today are numerical, spectral and bibliographic. Data representation by different schemes--relational, hierarchical and objects--is demonstrated. Quality index (QI) throws light on the quality of data. The objective, prospects and impact of database activity on expert systems are discussed. The number and size of corporate databases available on international networks crossed manageable number leading to databases about their contents. Subsets of corporate or small databases have been developed by groups of chemists. The features and role of knowledge-based or intelligent databases are described.

Artificial Intelligence↗
PubMed2004

Data mining challenges in the design of telemedicine platforms.

The evolution of telemedicine information systems involves the general processes of acquiring useful knowledge from medical data sets for diagnosis, intelligent efficient patient record transmission and autonomous adaptation of biomedical devices and their related software environments using quality of service attributes. Knowledge engineering concepts and methods allow application to the design of intelligent telemedicine platforms, satisfying the performance requirements and the quality assurance criteria of each specialized telemedicine application.

Artificial Intelligence↗
PubMed1995

Virtual reality and telepresence for military medicine.

The profound changes brought about by technology in the past few decades are leading to a total revolution in medicine. The advanced technologies of telepresence and virtual reality are but two of the manifestations emerging from our new information age; now all of medicine can be empowered because of this digital technology. The leading edge is on the digital battlefield, where an entire new concept in military medicine is evolving. Using remote sensors, intelligent systems, telepresence surgery and virtual reality surgical simulations, combat casualty care is prepared for the 21st century.

Artificial Intelligence↗
PubMed2003

Evaluation of inherent performance of intelligent medical decision support systems: utilising neural networks as an example.

Researchers who design intelligent systems for medical decision support, are aware of the need for response to real clinical issues, in particular the need to address the specific ethical problems that the medical domain has in using black boxes. This means such intelligent systems have to be thoroughly evaluated, for acceptability. Attempts at compliance, however, are hampered by lack of guidelines. This paper addresses the issue of inherent performance evaluation, which researchers have addressed in part, but a Medline search, using neural networks as an example of intelligent systems, indicated that only about 12.5% evaluated inherent performance adequately. This paper aims to address this issue by concentrating on the possible evaluation methodology, giving a framework and specific suggestions for each type of classification problem. This should allow the developers of intelligent systems to produce evidence of a sufficiency of output performance evaluation.

Artificial Intelligence↗
PubMedDate not supplied

An intelligent end-effector for a rehabilitation robot.

A UMI RTX robot, modified with limited end-effector sensors and a restricted but effective vision system, is currently used in a developmental education setting for severely physically disabled children. The low physical and cognitive abilities of the children involved in the project require a semi-autonomous robot with environmental sensing capability to operate in a task oriented mode. A variety of low-cost sensors including proximity, distance, force and slip sensors, have been investigated for integration in end-effectors for the RTX robot. The sensors employed on a modified end-effector are detailed and experimental results are presented. A design for an end-effector with integrated sensors is discussed. The integration of the sensor information into a high-level, task-oriented programming language is detailed and examples of high-level control sequences using sensor inputs are presented. Finally, the development of intelligent gripping strategies based on sensor information is discussed.

Artificial Intelligence↗
PubMed2001

Intelligent systems for nursing education.

Health care is one of the fastest growing areas in terms of care, treatment and the exploitation of new technology in Slovenia. There is a great need for new approaches ensuring that education and work of health care professionals will be built upon the state of the art in nursing. As a consequence the educational, governmental and "industrial" institutions from Slovenia, UK, Italy and Greece have determined to work on above problem. EU agreed to support the project under the Phare Tempus Framework and the aim of this paper is to present an educational approach based on intelligent systems and its application in nursing education.

Artificial Intelligence↗
PubMed2005

A framework for intelligent visualization of multiple time-oriented medical records.

Management of patients, especially chronic patients, requires presentation and processing of very large amounts of time-oriented clinical data. Using regular means such as text or tables is often ineffective, thus we propose to use the visual presentation of the information in decision support, especially in the medical domain. Displaying only raw data is not sufficient, because it still requires the user to derive meaningful conclusions from large amount of data. In order to support the computation process, we provide automated mechanisms for temporal abstraction. These mechanisms perform derivation of context-specific, interval-based abstract concepts from raw time-stamped clinical data, by using a domain-specific knowledge base. Then, these abstractions can be visualized and explored. In addition, in many cases (e.g. when comparing the effect of new drugs on various groups of patients) a view of multiple records is more effective than a view of each indi-vidual record separately. We have designed and implemented a system called VISITORS (VisualizatIon of Time-Oriented RecordS) which includes several tools for intelligent visualization and exploration of raw data and abstracted concepts for multiple patient records.

Abstracting and Indexing↗
PubMed2006

New trends in the virtualization of hospitals--tools for global e-Health.

The development of virtual hospitals and digital medicine helps to bridge the digital divide between different regions of the world and enables equal access to high-level medical care. Pre-operative planning, intra-operative navigation and minimally-invasive surgery require a digital and virtual environment supporting the perception of the physician. As data and computing resources in a virtual hospital are distributed over many sites the concept of the Grid should be integrated with other communication networks and platforms. A promising approach is the implementation of service-oriented architectures for an invisible grid, hiding complexity for both application developers and end-users. Examples of promising medical applications of Grid technology are the real-time 3D-visualization and manipulation of patient data for individualized treatment planning and the creation of distributed intelligent databases of medical images.

Artificial Intelligence↗