PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “Intelligent Systems”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

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

At least 91 records · Page 5Linked to original sources
PubMed1992

An intelligent computer-assisted instruction system designed for rural health workers in developing countries.

This paper describes an intelligent computer-assisted instruction system that was designed for rural health workers in developing countries. This system, called Consult-EAO, includes an expert module and a coaching module. The expert module, which is derived from the knowledge-based decision support system Tropicaid, covers most of medical practice in developing countries. It allows for the creation of outpatient simulations without the help of a teacher. The student may practice his knowledge by solving problems with these simulations. The system gives some initial facts and controls the simulation during the session by guiding the student toward the most efficient decisions. All student answers are analyzed and, if necessary, criticized. The messages are adapted to the situation due to the pedagogical rules of the coaching module. This system runs on PC-compatible computer.

Computer Simulation↗
PubMed1992

Diagnosis of periodontitis by physical measurement: interpretation from episodic disease hypothesis.

Physical measurements including the evaluation of probing depth, bleeding on probing, tooth mobility, and inflammation form the basis for most periodontal diagnostics in use today. The interpretation of these observations and the methods available for their measurement, however, have begun to change significantly. The episodic disease activity concept has done much to implement these changes. Observation of episodic attachment loss has been correlated with parallel radiographic changes, alteration in levels of probable pathogens, and changes in inflammatory mediator levels. The failure of pocket depth, suppuration, and bleeding on probing to predict episodic attachment loss has been given plausible explanations and enhanced meanings. Although attachment loss by a continuous process cannot be excluded in some disease conditions, the hypothesis of periodontal disease progression by episodic activity supplements and expands understanding of the disease process. Interest in periodontal diagnostics has accelerated in the last decade. As a parallel development, the technology of small computers has decreased in cost and increased in sophistication. The combination of these factors has created an environment for the development of intelligent diagnostic systems. Four commercially available systems and two systems under development are described. The systems, which measure pocket depth, pocket depth or attachment level, tooth mobility, and pocket temperature, all utilize computer processing of measurements. The result is to provide a simplified and more meaningful presentation of diagnostic information. As intelligent diagnostic systems prove themselves, some of these instruments are likely to become common to dental practice. The promise of more accurate identification of areas of the mouth that are diseased can increase both the efficiency and effectiveness of periodontal therapy.

Humans↗
PubMed1989

A knowledge-based information system for monitoring drug levels.

The expert system shell SMR has been enhanced to include information system routines for designing data screens and providing facilities for data entry, storage, retrieval, queries and descriptive statistics. The data for inference making is abstracted from the data base record and inserted into a data array to which the knowledge base is applied to derive the appropriate advice and comments. The enhanced system has been used to develop an intelligent information system for monitoring serum drug levels which includes evaluation of temporal changes and production of specialized printed reports. The module for digoxin has been fully developed and validated. To demonstrate the extension to other drugs a module for phenytoin was constructed with only a rudimentary knowledge base. Data from the request forms together with the S-digoxin results are entered into the data base by the department secretary. The day's results are then reviewed by the clinical pharmacologist. For each case, previous results may be displayed and are taken into account by the system in the decision process. The knowledge base is applied to the data to formulate an evaluative comment on the report returned to the requestor. The report includes a semi-graphic presentation of the current and previous results and either the system's interpretation or one entered by the pharmacologist if he does not agree with it. The pharmacologist's comment is also recorded in the data base for future retrieval, analysis and possible updating of the knowledge base. The system is now undergoing testing and evaluation under routine operations in the clinical pharmacology service. It is a prototype for other applications in both laboratory and clinical medicine currently under development at Uppsala University Hospital. This system may thus provide a vehicle for a more intensive penetration of knowledge-based systems in practical medical applications.

Data Interpretation, Statistical↗
PubMed1987

Computer technology: state of the art and future trends.

Computer technology and, more broadly, information technology, are bringing about a fundamental transformation in our society from an industrial economy to an information economy. A review of the short history and present state of information technology identifies two major undercurrents: the miniaturization of computer components, which has produced a millionfold increase in the complexity possible in a single chip of silicon, and the integration of four previously separate areas of information technology: computation, communication, databases and the user interface. Microelectronics, computer networks, data storage and user amenities are the basic technologies that support these four areas and stimulate their progress. Future trends in speech recognition, voice synthesis, artificial intelligence, expert systems, computational imaging and scientific workstations are also examined.

Artificial Intelligence↗
PubMed1988

A prototype system for perinatal knowledge engineering using an artificial intelligence tool.

Though several perinatal expert systems are extant, the use of artificial intelligence has, as yet, had minimal impact in medical computing. In this evaluation of the potential of AI techniques in the development of a computer based "Perinatal Consultant," a "top down" approach to the development of a perinatal knowledge base was taken, using as a source for such a knowledge base a 30-page manuscript of a chapter concerning high risk pregnancy. The UNIX utility "style" was used to parse sentences and obtain key words and phrases, both as part of a natural language interface and to identify key perinatal concepts. Compared with the "gold standard" of sentences containing key facts as chosen by the experts, a semiautomated method using a nonmedical speller to identify key words and phrases in context functioned with a sensitivity of 79%, i.e., approximately 8 in 10 key sentences were detected as the basis for PROLOG, rules and facts for the knowledge base. These encouraging results suggest that functional perinatal expert systems may well be expedited by using programming utilities in conjunction with AI tools and published literature.

Expert Systems↗
PubMed1991

RedSoar--a system for red blood cell antibody identification.

The primary goal of our research is to build an intelligent tutoring system for red blood cell antibody identification. In this paper, we describe the basis for a tutoring system--an expert system called RedSoar. RedSoar is built from two task-specific architectures that were designed for building flexible systems (i.e. systems that can use a variety of problem-solving strategies, and to which knowledge can easily-be added). RedSoar solves the antibody identification task correctly 81% of the time and new knowledge can be added in a straightforward manner. The system is capable of exhibiting human-like behavior which we believe is a necessary condition for building a successful tutoring system.

Blood Grouping and Crossmatching↗
PubMedDate not supplied

Expert systems for medical applications.

Expert systems, also known as intelligent knowledge based systems (IKBS), are computer programs which act as decision-support systems. They are currently being applied to a number of medical domains, most notably diagnosis and treatment planning. Their function is to assist the medical practitioner by giving ready access to the levels of skill shown by experts in a particular field. Much research effort has been expended but few systems have reached routine medical use. This paper presents a tutorial introduction to expert systems in medicine, explaining the basis of the technology, its current limitations and its prospective uses.

Expert Systems↗
PubMed1988

The effects of different frequency responses on sound quality judgments and speech intelligibility.

Four speech programs and two music programs were reproduced using five different frequency responses: one flat and the others combinations of reductions at lower frequencies and/or increases at higher frequencies. Twelve hearing impaired (HI) and 8 normal hearing (NH) subjects listened monaurally to the reproductions at comfortable listening level and judged the sound quality on seven perceptual scales and a scale for total impression. Speech intelligibility was measured for phonetically balanced (PB) word lists and for sentences in noise. Significant differences among the reproductions appeared in practically all scales. The most preferred system was characterized by a flat response at lower frequencies and a 6 dB/octave increase thereafter. There were certain differences between the NH and HI listeners in the judgments of the other systems. The intelligibility of PB word lists did not differ among the systems, and the S/N threshold for the sentences in noise only distinguished the flat response as worse than all others for the HI listeners. There was little correspondence between intelligibility measures and sound quality measures. The latter provided more information and distinctions among systems.

Adult↗
PubMedDate not supplied

Choice and explanation in medical management: a multiattribute model of artificial intelligence approaches.

This paper explores a model of choice and explanation in medical management and makes clear its advantages and limitations. The model is based on multiattribute decision making (MADM) and consists of four distinct strategies for choice and explanation, plus combinations of these four. Each strategy is a restricted form of the general MADM approach, and each makes restrictive assumptions about the nature of the domain. The advantage of tailoring a restricted form of a general technique to a particular domain is that such efforts may better capture the character of the domain and allow choice and explanation to be more naturally modelled. The uses of the strategies for both choice and explanation are illustrated with analyses of several existing medical management artificial intelligence (AI) systems, and also with examples from the management of primary breast cancer. Using the model it is possible to identify common underlying features of these AI systems, since each employs portions of this model in different ways. Thus the model enables better understanding and characterization of the seemingly ad hoc decision making of previous systems.

Algorithms↗
PubMed1991

A multimedia Anatomy Browser incorporating a knowledge base and 3D images.

We describe a multimedia program for teaching anatomy. The program, called the Anatomy Browser, displays cross-sectional and topographical images, with outlines around structures and regions of interest. The user may point to these structures and retrieve text descriptions, view symbolic relationships between structures, or view spatial relationships by accessing 3-D graphics animations from videodiscs produced specifically for this program. The software also helps students exercise what they have learned by asking them to identify structures by name and location. The program is implemented in a client-server architecture, with the user interface residing on a Macintosh, while images, data, and a growing symbolic knowledge base of anatomy are stored on a fileserver. This architecture allows us to develop practical tutorial modules that are in current use, while at the same time developing the knowledge base that will lead to more intelligent tutorial systems.

Anatomy↗
PubMed1988

Knowledge-based educational systems.

In knowledge-based educational systems, the key concept is that information and procedures are represented in the same data structure. These structures can search for each other in flexible and, consequently, very robust ways. At the Air Force Human Resources Laboratory (AFHRL), our researchers are building computer environments that know what they know, know how people can best use them, and know how to draw inferences about their state--self-referential electronic tutors. In September 1986, artificial intelligence researchers participated in AFHRL's Research Planning Forum for Intelligent Tutorial Systems (ITS). This essay reviews the state of the philosophy, art, and science of artificial intelligence (AI) approaches to education. Then it summarizes the research issues which were presented, discussed, and better defined in this Forum--namely the nature and representation of 1) expertise modules, 2) student diagnostic modules, 3) adaptive instructional and curriculum modules, 4) instructional environments, and 5) man-machine interfaces. Advances in artificial intelligence, cognitive science, and instructional discourse have provided a means for investigating human learning, for representing an individual's own "knowledge processing." Research and development in knowledge-based educational systems seems promising, not only for helping people learn how to perform complex tasks, but also for explicitly expressing how people learn to learn. Therefore, would it not be wise to establish a scientific legacy for the development of effective knowledge-based tutorial systems which is informed by the best studies of mind and meaning, language and thought, purpose and paradox?

Artificial Intelligence↗
PubMed1987

Wechsler Intelligence Scale profiles, the cholinergic system, and Alzheimer's disease.

Forty-one patients with putative Alzheimer's Disease (AD) were evaluated to determine the diagnostic utility of a profile of Wechsler Adult Intelligence Scale (WAIS) subtests which has been proposed by Fuld (1984) to identify cholinergic dysfunction. Only nine (21.9%) of these patients had positive Wechsler profiles. Half (n = 21) of the AD patients had been given the WAIS, and the other half (n = 20) the Wechsler Adult Intelligence Scale-Revised (WAIS-R). Positive profiles occurred more often in the AD subgroup given the WAIS-R, but this difference was not statistically significant. Specificity of the formula was evaluated using Wechsler results of 42 older normals and 30 patients who were being evaluated for dementia but who did not have AD. One of the 42 normals (2.4%) and five of the patient controls (16.7%) showed a positive Wechsler profile. Because of the Fuld formula's low sensitivity, a negative Wechsler profile cannot be used to help rule out AD. Although specificity of the formula is high, the diagnostic value of a positive Wechsler profile is modest even under the most favorable AD baserate conditions.

Aged↗
PubMed1986

Future programs at the National Library of Medicine.

The future of the National Library of Medicine will be shaped by a number of scientific, technical, and social influences. Among these are the continuing rapid development of computer technology and storage systems. Artificial intelligence techniques, factual databases, the emergence of medical informatics as a formal discipline, and the development of Integrated Academic Information Management Systems (IAIMS) are also important influences on the direction of the library. Public policy issues will influence the future of NLM--among them, sharing of scientific information between nations and the role of federal agencies in dissemination of information domestically. The formal, long-range plan now being prepared for the library by panels of expert advisers will be a guide for future programs and goals.

Artificial Intelligence↗
PubMed1988

Intelligent computer-based assessment and psychotherapy. An expert system for sexual dysfunction.

New and converging developments in the areas of artificial intelligence, intelligent tutoring systems, and cognitive therapy have made possible a new approach to computer-assisted assessment and psychotherapy. This new approach combines the capacity for intelligent therapeutic dialogue with the presentation of individualized therapeutic interventions. Previous attempts at computerized psychotherapy are reviewed to highlight a newly developed rule-based expert system, Sexpert, which assesses and treats sexual dysfunction. Preliminary observations concerning couples' reaction to and acceptance of Sexpert are presented.

Artificial Intelligence↗
PubMed1988

Technical intuition in system diagnosis, or accessing the libraries of the mind.

Expert diagnosticians draw upon rich, integrated structures of knowledge and associated action rules to achieve their prodigious performances. Studies in both medical diagnosis and electronic troubleshooting have revealed that it is particularized knowledge that plays a vital role for experts in both domains, not inexplicable powers of intuition. Advanced knowledge engineering methods have been developed and applied in a number of Air Force technical domains so that experts' mental databases and procedural libraries can be made explicit enough to serve as targets of instruction. Instructional principles have been derived from this knowledge engineering work and are guiding the development of a new generation of Air Force technical training systems. The training dictum is to teach from realistic cases so that theory of system operation and specialized solution methods are taught in tandem. The learning environments will further foster the welding of factual knowledge to action rules by providing "assisted laboratory" experiences via intelligent tutoring systems. In these environments, trainees can practice carrying out diagnoses on increasingly complex problems with the help of an articulate expert coach.

Expert Systems↗
PubMed2026

CAUSAL artificial intelligence and data-driven decision intelligence in personalized medicine: a review of healthcare informatics systems.

This review examines the integration of causal artificial intelligence (AI) and data-driven decision intelligence within healthcare informatics systems to advance personalized medicine and clinical decision-making. A narrative review methodology was employed, synthesizing interdisciplinary literature from major databases, including PubMed, Scopus, Web of Science, IEEE Xplore, and ScienceDirect. Studies focusing on causal inference, decision intelligence, and healthcare informatics applications in personalized medicine were included. Data were extracted on methodological approaches, healthcare settings, analytical techniques, and clinical applications, followed by thematic synthesis. Findings indicate that causal AI enhances clinical decision support by enabling estimation of treatment effects and simulation of intervention outcomes at the individual patient level. Integration of multimodal health data such as electronic health records, genomic data, and real-time monitoring improves prediction accuracy and supports tailored treatment strategies. Additionally, causal models improve interpretability, fostering clinician trust and facilitating transparent decision-making. Robust healthcare informatics infrastructures, including interoperable systems and data warehouses, were identified as critical enablers of causal analytics. Overall, causal AI represents a transformative advancement in healthcare analytics, supporting more informed, individualized, and evidence-based clinical decisions. Its integration within healthcare informatics systems has significant potential to improve patient outcomes and guide the future of intelligent, personalized healthcare delivery.

Precision Medicine↗