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PubMed2002

[Mobile autonomous robots-Possibilities and limits].

Besides industrial robots, which today are firmly established in production processes, service robots are becoming more and more important. They shall provide services for humans in different areas of their professional and everyday environment including medicine. Most of these service robots are mobile which requires an intelligent autonomous behaviour. After characterising the different kinds of robots the relevant paradigms of intelligent autonomous behaviour for mobile robots are critically discussed in this paper and illustrated by three concrete examples of robots realized in Lübeck. In addition a short survey of actual kinds of surgical robots as well as an outlook to future developments is given.

Artificial Intelligence↗
PubMedDate not supplied

Computer analysis of the fetal heart rate.

Computer analysis of the fetal heart rate is a technology of the Information Age commercially available for research and clinical practice. Intelligent systems are engineered with algorithms or neural networks designed to simulate expert knowledge. Automated analysis has provided objective, standardized, and reproducible data used to research fetal heart rate responses in the antepartum and intrapartum setting. Perinatal information systems can integrate FHR analysis and data management.

Algorithms↗
PubMed1998

Modern architectures for intelligent systems: reusable ontologies and problem-solving methods.

When interest in intelligent systems for clinical medicine soared in the 1970s, workers in medical informatics became particularly attracted to rule-based systems. Although many successful rule-based applications were constructed, development and maintenance of large rule bases remained quite problematic. In the 1980s, an entire industry dedicated to the marketing of tools for creating rule-based systems rose and fell, as workers in medical informatics began to appreciate deeply why knowledge acquisition and maintenance for such systems are difficult problems. During this time period, investigators began to explore alternative programming abstractions that could be used to develop intelligent systems. The notions of "generic tasks" and of reusable problem-solving methods became extremely influential. By the 1990s, academic centers were experimenting with architectures for intelligent systems based on two classes of reusable components: (1) domain-independent problem-solving methods-standard algorithms for automating stereotypical tasks--and (2) domain ontologies that captured the essential concepts (and relationships among those concepts) in particular application areas. This paper will highlight how intelligent systems for diverse tasks can be efficiently automated using these kinds of building blocks. The creation of domain ontologies and problem-solving methods is the fundamental end product of basic research in medical informatics. Consequently, these concepts need more attention by our scientific community.

Algorithms↗
PubMed2004

Evolving rule-based systems in two medical domains using genetic programming.

OBJECTIVE: To demonstrate and compare the application of different genetic programming (GP) based intelligent methodologies for the construction of rule-based systems in two medical domains: the diagnosis of aphasia's subtypes and the classification of pap-smear examinations. MATERIAL: Past data representing (a) successful diagnosis of aphasia's subtypes from collaborating medical experts through a free interview per patient, and (b) correctly classified smears (images of cells) by cyto-technologists, previously stained using the Papanicolaou method. METHODS: Initially a hybrid approach is proposed, which combines standard genetic programming and heuristic hierarchical crisp rule-base construction. Then, genetic programming for the production of crisp rule based systems is attempted. Finally, another hybrid intelligent model is composed by a grammar driven genetic programming system for the generation of fuzzy rule-based systems. RESULTS: Results denote the effectiveness of the proposed systems, while they are also compared for their efficiency, accuracy and comprehensibility, to those of an inductive machine learning approach as well as to those of a standard genetic programming symbolic expression approach. CONCLUSION: The proposed GP-based intelligent methodologies are able to produce accurate and comprehensible results for medical experts performing competitive to other intelligent approaches. The aim of the authors was the production of accurate but also sensible decision rules that could potentially help medical doctors to extract conclusions, even at the expense of a higher classification score achievement.

Aphasia↗
PubMed2004

Cognitive human factors for telemedicine systems.

The recent integration of telephony systems with information and communication technology (ICT) enables the development of innovative tools for telemedicine. The dissemination and widespread acceptance of telephone-based care monitoring systems challenge the researcher to deal with the cognitive factors involved in the patient-physician interaction, and the way they should be to shape up the technological solutions. This paper proposes a model that describes the impact of socio-cognitive factors in the complex process of health care management. The model has been used to design and develop a telephone system for the management of hypertensive patient within the EU funded Homey project. The knowledge existed in a widely accepted guideline for the care of hypertension has been represented and augmented through the proposed cognitive model. The final product is an intelligent system able to manage an adaptive dialogue. It monitors patients' adherence and increases their involvement by promoting self-care through frequent virtual visits, which is complementary to the traditional face-to-face encounters with their primary care physicians.

Artificial Intelligence↗
PubMed1998

[The development of an intelligent four-channel aggregometer].

The paper introduces the hardware and software design of the instrument. We use 89C52 single-chip computer as the microprocessor to control the amplifier, AD and DA conversion chip to realize the sampling, data process, printout and supervision. The final result is printed out in form of data and aggregation curve from PP40 plotter.

Artificial Intelligence↗
PubMed2003

Implementation and evaluation of an virtual intelligent agent.

Reference librarians at the National Library of Medicine answer over 100,000 client questions annually. Although many answers are the NLM Web, clients may have difficulty finding them. Using intelligent virtual agent software, the NLM launched Cosmo, the Customer Service Owl (http://wwwns.nlm.nih.gov/). Cosmo uses natural language pattern matching to answer common questions. Early evaluation shows Cosmo can answer 25% of questions asked, but some users mistake the service for chat reference or a search engine.

Artificial Intelligence↗
PubMed2003

Towards knowledge-based systems in clinical practice: development of an integrated clinical information and knowledge management support system.

Given that clinicians presented with identical clinical information will act in different ways, there is a need to introduce into routine clinical practice methods and tools to support the scientific homogeneity and accountability of healthcare decisions and actions. The benefits expected from such action include an overall reduction in cost, improved quality of care, patient and public opinion satisfaction. Computer-based medical data processing has yielded methods and tools for managing the task away from the hospital management level and closer to the desired disease and patient management level. To this end, advanced applications of information and disease process modelling technologies have already demonstrated an ability to significantly augment clinical decision making as a by-product. The wide-spread acceptance of evidence-based medicine as the basis of cost-conscious and concurrently quality-wise accountable clinical practice suffices as evidence supporting this claim. Electronic libraries are one-step towards an online status of this key health-care delivery quality control environment. Nonetheless, to date, the underlying information and knowledge management technologies have failed to be integrated into any form of pragmatic or marketable online and real-time clinical decision making tool. One of the main obstacles that needs to be overcome is the development of systems that treat both information and knowledge as clinical objects with same modelling requirements. This paper describes the development of such a system in the form of an intelligent clinical information management system: a system which at the most fundamental level of clinical decision support facilitates both the organised acquisition of clinical information and knowledge and provides a test-bed for the development and evaluation of knowledge-based decision support functions.

Artificial Intelligence↗
PubMed2003

Tools for intelligent control: fuzzy controllers, neural networks and genetic algorithms.

The goal of this expository paper is to bring forth the basic current elements of soft computing (fuzzy logic, neural networks, genetic algorithms and genetic programming) and the current applications in intelligent control. Fuzzy sets and fuzzy logic and their applications to control systems have been documented. Other elements of soft computing, such as neural networks and genetic algorithms, are also treated for the novice reader. Each topic will have a number of relevant references of as many key contributors as possible.

Algorithms↗
PubMedDate not supplied

An intelligent system approach to higher-dimensional classification of volume data.

In volume data visualization, the classification step is used to determine voxel visibility and is usually carried out through the interactive editing of a transfer function that defines a mapping between voxel value and color/opacity. This approach is limited by the difficulties in working effectively in the transfer function space beyond two dimensions. We present a new approach to the volume classification problem which couples machine learning and a painting metaphor to allow more sophisticated classification in an intuitive manner. The user works in the volume data space by directly painting on sample slices of the volume and the painted voxels are used in an iterative training process. The trained system can then classify the entire volume. Both classification and rendering can be hardware accelerated, providing immediate visual feedback as painting progresses. Such an intelligent system approach enables the user to perform classification in a much higher dimensional space without explicitly specifying the mapping for every dimension used. Furthermore, the trained system for one data set may be reused to classify other data sets with similar characteristics.

Algorithms↗
PubMed1999

Intelligent systems in medical diagnosis.

From an intelligent system for a computer supported medical diagnosis it is expected to achieve high accuracy and ability to draw conclusions from a small data sets. Medical practice could takes many years to generate a large database. A new mathematical method that is able to learn on a small data set is presented.

Algorithms↗
PubMed2002

Leveraging XML-based electronic medical records to extract experiential clinical knowledge. An automated approach to generate cases for medical case-based reasoning systems.

Case-based reasoning (CBR)-driven medical diagnostic systems demand a critical mass of up-to-date diagnostic-quality cases that depict the problem-solving methodology of medical experts. In practical terms, procurement of CBR-compliant cases is quite challenging, as this requires medical experts to map their experiential knowledge to an unfamiliar computational formalism. In this paper, we propose a novel medical knowledge acquisition approach that leverages routinely generated electronic medical records (EMRs) as an alternate source for CBR-compliant cases. We present a methodology to autonomously transform XML-based EMR to specialized CBR-compliant cases for CBR-driven medical diagnostic systems. Our multi-stage methodology features: (a) collection of heterogeneous EMR from Internet-accessible EMR repositories via intelligent agents, (b) automated transformation of both the structure and content of generic EMR to specialized CBR-compliant cases, and (c) inductive estimation of the weight of each case-defining attribute. The computational implementation of our methodology is presented as case acquisition and transcription info-structure (CATI).

Artificial Intelligence↗
PubMed2005

Feasibility of an intelligent tutoring system for laboratory medicine.

Laboratory medicine is not adequately addressed in most medical school curricula. A review of the literature was performed to evaluate the feasibility of an intelligent tutoring system to enhance laboratory medicine training. This appraisal suggests that such a system must integrate basic science and clinical training. A system equipped with a clinical knowledgebase, in the form of an expert system, and a pathophysiology knowledgebase, in the form of multiple semantic networks, could provide such integration.

Artificial Intelligence↗
PubMed2005

Evolving telemedicine/ehealth technology.

This paper describes emerging technologies to support a rapidly changing and expanding scope of telemedicine/telehealth applications. Of primary interest here are wireless systems, emerging broadband, nanotechnology, intelligent agent applications, and grid computing. More specifically, the paper describes the changes underway in wireless designs aimed at enhancing security; some of the current work involving the development of nanotechnology applications and research into the use of intelligent agents/artificial intelligence technology to establish what are termed "Knowbots"; and a sampling of the use of Web services, such as grid computing capabilities, to support medical applications. In addition, the expansion of these technologies and the need for cost containment to sustain future health care for an increasingly mobile and aging population is discussed.

Algorithms↗
PubMed1993

Inference of order in genetic systems.

We survey and discuss issues required of intelligent systems to support research efforts in locus mapping. In particular we focus on the issues of order, on how one can automate the reasoning processes of ordering, and the database structures required to support orders, including ambiguity and uncertainty. We conclude with a summary of work to be done.

Animals↗
PubMed1996

Building intelligent alarm systems by combining mathematical models and inductive machine learning techniques Part 2--sensitivity analysis.

In an earlier study an approach was described to generate intelligent alarm systems for monitoring ventilation of patients via mathematical simulation and machine learning. However, ventilator settings were not varied. In this study we investigated whether an alarm system could be created with which a satisfactory classification performance could be obtained under a wide variety of ventilator settings, by varying inspiratory to expiratory time (I:E) ratio, tidal volume and respiratory rate. In a first experiment three patient data sets were modeled, each with a different I:E ratio. A part of each data set was used to construct an alarm system for each I:E ratio. The remaining part was used to test the performance of the alarm systems. The three training sets were also combined to construct one alarm system, which was tested with the three test sets. Finally, all alarm systems were tested with data generated by a patient simulator. Similar experiments were performed for the tidal volume and the respiratory rate. It was concluded that an optimally functioning alarm system should contain a library of rule sets, one for each set of ventilator settings. A second best alternative is to take all possible settings into consideration when constructing the training set. Classification performance of the trees that were trained with multiple ventilator settings ranged from 98 to 100% for all test sets. When tested with the independent patient simulator data the classification performance of these trees ranged from 80 to 100%.

Airway Resistance↗
PubMed2002

Disruptive visions.

Numerous advanced technologies, both medical and nonmedical, are emerging faster than their social, behavioral, political, moral, and ethical implications can be understood. Some of these technologies will fundamentally challenge the practice of surgery: human cloning, genetic engineering, tissue engineering, intelligent robotics, nanotechnology, suspended animation, regeneration, and species prolongation. Because of the rapidity of change, the current status of these emerging technologies with their specific moral and ethical issues must be addressed at this time by the new generation of surgeons, or we must all face the consequences of an uncontrolled and unprepared future.

Animals↗
PubMed1992

Computers as clinicians: an update.

Computers as clinicians entered medical settings relatively recently, but with limited success because they lack general intelligence--that is, though they can be experts in domain specific specialties, they cannot yet deal with clinical problems never before encountered. SOAR, a novel AI computer programming architecture, can learn from past encounters with prior problems and can generalize its learning to new ones. It may therefore take computers to a higher level of clinical performance.

Artificial Intelligence↗