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At least 613 records · Page 34Linked to original sources
PubMed1986

Comparison of amplification systems in an auditorium.

Intelligibility of speech at two positions in a large auditorium was compared for the public address system (PA) and two assistive listening systems: Frequency modulation of radio frequencies (FM) and modulation of infrared light waves (IR). Listening groups were: normal-hearing adults, hearing-impaired, hearing aid users, elderly, and non-native. Word-identification scores were obtained with the Modified Rhyme Tests. Analysis of variance indicated that the main effects of systems, groups, and listening position were significant. Also significant were the two-way interactions. For all groups, the assistive listening systems provided better scores than the PA system. The difference between the two systems was statistically significant, but very small. It can be concluded that both listening systems provide improved speech intelligibility for various types of listeners.

Acoustic Stimulation↗
PubMed1999

Ethnographic interviews to elicit patients' reactions to an intelligent interactive telephone health behavior advisor system.

Information technology is being used to collect data directly from patients and to provide educational information to them. Concern over patient reactions to this use of information technology is especially important in light of the debate over whether computers dehumanize patients. This study reports reactions that patient users expressed in ethnographic interviews about using a computer-based telecommunications system. The interviews were conducted as part of a larger evaluation of Telephone-Linked Care (TLC)-HealthCall, an intelligent interactive telephone advisor, that advised individuals about how to improve their health through changes in diet or exercise. Interview findings suggest that people formed personal relationships with the TLC system. These relationships ranged from feeling guilty about their diet or exercise behavior to feeling love for the voice. The findings raise system design and user interface issues as well as research and ethical questions.

Anthropology, Cultural↗
PubMed1997

Automated analysis of protein NMR assignments using methods from artificial intelligence.

An expert system for determining resonance assignments from NMR spectra of proteins is described. Given the amino acid sequence, a two-dimensional 15N-1H heteronuclear correlation spectrum and seven to eight three-dimensional triple-resonance NMR spectra for seven proteins, AUTOASSIGN obtained an average of 98% of sequence-specific spin-system assignments with an error rate of less than 0.5%. Execution times on a Sparc 10 workstation varied from 16 seconds for smaller proteins with simple spectra to one to nine minutes for medium size proteins exhibiting numerous extra spin systems attributed to conformational isomerization. AUTOASSIGN combines symbolic constraint satisfaction methods with a domain-specific knowledge base to exploit the logical structure of the sequential assignment problem, the specific features of the various NMR experiments, and the expected chemical shift frequencies of different amino acids. The current implementation specializes in the analysis of data derived from the most sensitive of the currently available triple-resonance experiments. Potential extensions of the system for analysis of additional types of protein NMR data are also discussed.

Automation↗
PubMed1993

Integrating knowledge-based systems and databases.

In recent years, there has been an explosion of interest among the computing community in the field of artificial intelligence, particularly in the areas of natural language processing and knowledge-based systems (KBS). The medical domain has seen the development of hundreds of KBSs and there is substantial evidence to show that the application of a knowledge-based approach to decision support can go a long way towards overcoming the information overload experienced by many clinicians today. Yet many of these medical KBSs are still at the prototype stage and are mainly confined to research laboratories. There are many reasons for this apparently slow take-up of the technology, but one of the most significant is the lack of integration into the regular routine information processing of the organisation, in particular the database processing. This paper discusses the benefits of such integration and methods for achieving it in the context of general trends in information systems. Database technology provides efficient and secure management of large amounts of data in a multi-user, multi-application environment. Knowledge-based technology, on the other hand, provides mechanisms for building intelligent systems. Thus, for example, given a set of facts about a domain (symptoms, laboratory test results, etc.) together with a set of rules which apply to that domain (e.g. 'if TT4 > 150 nmol/l then suspect hyperthyroidism'), a KBS can deduce new information about that domain automatically. The effective integration of these two technologies is seen as a means of achieving the intelligent information systems of the future. There are three basic approaches to integrating KBSs and databases. The first is to start with the KBS and incorporate data management functions. Alternatively, intelligence from the KBS can be incorporated into the database. Finally, the two systems can be allowed to co-exist as independent systems which can talk to each other by means of standard interfaces. There are many advantages to this last approach since it offers much more flexibility and extensibility and is consistent with the general trend in computing towards open systems.

Artificial Intelligence↗
PubMed2001

Extended time-to-collision measures for road traffic safety assessment.

This article describes two new safety indicators based on the time-to-collision notion suitable for comparative road traffic safety analyses. Such safety indicators can be applied in the comparison of a do-nothing case with an adapted situation, e.g. the introduction of intelligent driver support systems. In contrast to the classical time-to-collision value, measured at a cross section, the improved safety indicators use vehicle trajectories collected over a specific time horizon for a certain roadway segment to calculate the overall safety indicator value. Vehicle-specific indicator values as well as safety-critical probabilities can easily be determined from the developed safety measures. Application of the derived safety indicators is demonstrated for the assessment of the potential safety impacts of driver support systems from which it appears that some Autonomous Intelligent Cruise Control (AICC) designs are more safety-critical than the reference case without these systems. It is suggested that the indicator threshold value to be applied in the safety assessment has to be adapted when advanced AICC-systems with safe characteristics are introduced.

Accidents, Traffic↗
PubMed2001

[Evaluation of systemic activity of the brain by means of an artificial intelligence model].

The model based on the systems representation of informational brain mechanisms reproduces the principal stages of intellectual activities: afferent synthesis, decision making, acceptor of results of actions. The imitation of behavior of subjects in the special experimental environment with the model allows quantitative estimation of parameters of systemic stages in normal subjects of different ages and subjects with different brain dysfunctions, such as arteriosclerosis, schizophrenia, etc.

Adolescent↗
PubMed2002

Interaction of speech coders and atypical speech I: effects on speech intelligibility.

We investigated how standard speech coders, currently used in modern communication systems, affect the intelligibility of the speech of persons who have common speech and voice disorders. Three standardized speech coders (viz., GSM 6.10 [RPE-LTP], FS1016 [CELP], FS1015 [LPC]) and two speech coders based on subband processing were evaluated for their performance. Coder effects were assessed by measuring the intelligibility of vowels and consonants both before and after processing by the speech coders. Native English talkers who had normal hearing identified these speech sounds. Results confirmed that (a) all coders reduce the intelligibility of spoken language; (b) these effects occur in a consistent manner, with the GSM and CELP coders providing the least degradation relative to the original unprocessed speech; and (c) coders interact with individual voices so that speech is degraded differentially for different talkers.

Adult↗
PubMed1991

[A new database system for radiological reports].

We have designed and developed a new database system to facilitate automatic feedback of the content of radiology reports to radiologists. The prototype of this database system has been implemented in the RGSS-IDJ, a developmental computer system that applies artificial intelligence methods to a reporting system. This prototype system was constructed to test the feasibility of overcoming the limitations of conventional database systems. The new database system is based on our semantic model for radiology reports and is able to treat data with unnormalized relations. Operations specific to our database system include the ability to acquire information about a set of reports that contains any semantic expression included in the lexicon and the ability to obtain the expressions that belong to a set of several semantic expressions in the reports. Thus, our new database system will offer a more powerful tool for analyzing the content of reports than conventional database systems.

Databases, Bibliographic↗
PubMed1995

Automated classification of encounter notes in a computer based medical record.

Harvard Community Health Plan is exploring emerging information technologies for means to use the text portion of its 25 year old computerized medical record system. The Center for Intelligent Information Retrieval is developing systems to answer the question: to what extent can automated information systems replace manual chart review of encounter notes? INQUERY, a probabilistic inference net information retrieval system, and FIGLEAF, an inductive decision tree text classifier are applied to the problem of classifying electronic encounter notes to identify acute exacerbations in pediatric asthmatics. Both systems achieve average precisions of greater than 80%, with a new enhancement to INQUERY's relevance feedback, the top performer. Refinement of the systems and plans for their integration are discussed.

Asthma↗
PubMed2003

Personal relationships with an intelligent interactive telephone health behavior advisor system: a multimethod study using surveys and ethnographic interviews.

The burgeoning of consumer health informatics and virtual health care can help people improve their health. However, little is known about individuals' reactions to such systems. We conducted an evaluation of the telephone-linked care (TLC) system, a computer-based telecommunications system, that functions as an at home monitor, educator, and counselor for patients with chronic health conditions. Our multimethod assessment of individuals' reactions to using TLC included both quantitative and qualitative methods. Ethnographic in-depth open-ended interviews indicated more subtle and surprising reactions to TLC than the overall positive responses from surveys: individuals formed personal relationships with this technology. This relationship formation suggests that TLC designers may have been successful in their attempts to emulate a conversation with a human being. Our study adds to evidence that technology can serve as a projective device for peoples' values and psychological issues. Both designers and users project values and goals onto computer-based technologies and take on different identities through it. Different groups of users, therefore, may see the same technology differently. People also form relationships with technologies, as they did with TLC. These findings, as well as implications for system design and health outcomes, need to be explored in additional studies.

Adult↗
PubMed1995

Triplet code-independent programming of living systems organisation by DNA: the link with intelligence and memory.

Previous suggestions from this laboratory (3), (a) that within its molecular electronic structure, DNA houses a computer-analog program of immense complexity, operating independently of, but complementary to, triplet coding and (b) that, inter alia, this program is the driving force for organising and executing the construction of species individuals in three dimensions, are extended in the present communication. It is now concluded that the DNA program also embodies an 'intelligence' component, which extends its organising ability both qualitatively and quantitatively beyond any of the heavily circumscribed 'self-organising' attributes claimed to be associated with naturally occurring inanimate systems. Further, that as part of the developmental process, a program component organises the fabrication of mammalian central nervous systems, including that of human beings with the associated attributes of intelligence, creativity and constructional skills. It is further suggested that the sophisticated random access memory system associated with human beings in particular may be explicable in terms of an extension of the DNA programming system: basically this involves the latter operating as computer-type 'hardware' for the storage of long-term memory and interacting with, primarily, glial cell RNA, acting as 'software' and storing short term traces. Finally, it is suggested that such an interrelationship between DNA/RNA molecular electronic structures can provide the necessary memory storage capacity and flexibility and also facilitates random access to the long-term DNA memory store.

Animals↗
PubMed1993

Exploring the relationship between rationality and bounded rationality in medical knowledge-based systems.

If our goal in Artificial Intelligence in Medicine (AIM) is to engineer systems health-care providers will both use and, in the process, improve their performance, we must concentrate on the development of causal theories of knowledge and problem solving. One broad direction in pursuing this goal is understanding the relationships between existing models of rationality and bounded rationality for similar tasks. Models of rationality refer to those approaches in which the optimal properties of the models are deductively provable, i.e. in which the processing is rational. Representative models of rationality used in AIM are deductive logical models, statistical models such as Bayesian inference models, and decision-analytic models. Models of bounded rationality are those which do not guarantee such optimal properties nor yield to deductive correctness proofs. These models have their roots in cognitive psychology. In this article we show how explicating the relationship between models of rationality and bounded rationality might be done in the case of abductive tasks in medicine. This is done by positioning these modeling approaches within the same framework (an abstract computational model) and interpreting in this context both computational complexity results concerning the nature of the task and empirical results studies of human problem-solving behavior.

Artificial Intelligence↗
PubMedDate not supplied

[Use of psychopathometric procedures in diagnosis of dementia exemplified by a comparison between the Mini-Mental State and the MWT/KAI (Multiple-Choice Vocabulary/General Intelligence Test Short-Form) test system].

Different definitions of dementia have resulted in various psychopathometric diagnostic instruments. For that reason, the validity of the test or test battery is related to the originating definition of dementia. There are short tests which can be easily handled (e.g., Mini-Mental State or the test battery Multiple-Choice-Vocabulary-Intelligence Test/Short Test for General Intelligence). These tests can be used for the verification of a severe intellectual and mnemonic deterioration or a relative decrease of the mental capacity. For their objectivity, reliability and validity they are suitable for diagnostic routine. However, two aspects should be taken into consideration: Before using psychopathometric tests which aim at objectifying a decrease of mental capacity and indicating the degree of severity, it is necessary to make a differential diagnosis for particularly excluding so-called pseudodementia. It is also a fact that a single test is not sufficient for registering each degree of severity. The Mini-Mental State test can be used for documenting moderate to severe cases of dementia. The test battery Multiple-Choice-Vocabulary-Intelligence Test (MWT)/Short Test for General Intelligence (KAI) is suitable for the diagnosis and follow-up of mild to moderate cases.

Aged↗
PubMed2005

Artificial intelligence and robotics in high throughput post-genomics.

The shift of post-genomics towards a systems approach has offered an ever-increasing role for artificial intelligence (AI) and robotics. Many disciplines (e.g. engineering, robotics, computer science) bear on the problem of automating the different stages involved in post-genomic research with a view to developing quality assured high-dimensional data. We review some of the latest contributions of AI and robotics to this end and note the limitations arising from the current independent, exploratory way in which specific solutions are being presented for specific problems without regard to how these could be eventually integrated into one comprehensible integrated intelligent system.

Artificial Intelligence↗
PubMed2006

AutoNR: an automated system that measures ECAP thresholds with the Nucleus Freedom cochlear implant via machine intelligence.

OBJECTIVE: AutoNRT is an automated system that measures electrically evoked compound action potential (ECAP) thresholds from the auditory nerve with the Nucleus Freedom cochlear implant. ECAP thresholds along the electrode array are useful in objectively fitting cochlear implant systems for individual use. This paper provides the first detailed description of the AutoNRT algorithm and its expert systems, and reports the clinical success of AutoNRT to date. METHODS: AutoNRT determines thresholds by visual detection, using two decision tree expert systems that automatically recognise ECAPs. The expert systems are guided by a dataset of 5393 neural response measurements. The algorithm approaches threshold from lower stimulus levels, ensuring recipient safety during postoperative measurements. Intraoperative measurements use the same algorithm but proceed faster by beginning at stimulus levels much closer to threshold. When searching for ECAPs, AutoNRT uses a highly specific expert system (specificity of 99% during training, 96% during testing; sensitivity of 91% during training, 89% during testing). Once ECAPs are established, AutoNRT uses an unbiased expert system to determine an accurate threshold. Throughout the execution of the algorithm, recording parameters (such as implant amplifier gain) are automatically optimised when needed. RESULTS: In a study that included 29 intraoperative and 29 postoperative subjects (a total of 418 electrodes), AutoNRT determined a threshold in 93% of cases where a human expert also determined a threshold. When compared to the median threshold of multiple human observers on 77 randomly selected electrodes, AutoNRT performed as accurately as the 'average' clinician. CONCLUSIONS: AutoNRT has demonstrated a high success rate and a level of performance that is comparable with human experts. It has been used in many clinics worldwide throughout the clinical trial and commercial launch of Nucleus Custom Sound Suite, significantly streamlining the clinical procedures associated with cochlear implant use.

Algorithms↗
PubMedDate not supplied

Techniques in evaluating nursing expert systems: A case study.

This study addresses the problems in evaluating nursing diagnostic artificial intelligence (AI) expert systems. Two separate experiments (N = 49) were conducted using a computer expert system. The first experiment, the "white box" experiment (n = 9), compared the diagnostic techniques applied by experience RNs against the programmed techniques used by the expert system. The second experiment, the "black box" experiment (n = 40), compared diagnostic results of beginning nurses against the computer expert systems results. In some cases the computer outperformed the nurses and vice versa. The evaluation techniques, as applied in both experiments, enhance the ability of nurses to evaluate and select AI expert systems to be used in computer-assisted diagnosis of nursing problems.

Clinical Competence↗
PubMed1997

Using a general theory of time and change in patient monitoring: experiment and evaluation.

In this paper, we propose to use one of the well-known general theories of time and change, namely the Event Calculus (Kowalski and Sergot, New Generation Computing 4, 67-95, 1986), to represent temporal aspects in intelligent medical monitoring systems. In particular, we explore the application of CEC (Chittaro and Montanari, Computational Intelligence 12, 359-382, 1996) (an efficient implementation of the Event Calculus) to the management of mechanical ventilation. First, we present the prototype we have built, which has been extensively tested on patient's data from real clinical cases. Then, we provide a thorough evaluation of the obtained results, pointing out both strengths and weaknesses of the approach, and identifying a number of extensions which can be extremely useful to scale up the medical application of the approach.

Artificial Intelligence↗