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At least 523 records · Page 29Linked to original sources
PubMed2006

Implementing tutoring strategies into a patient simulator for clinical reasoning learning.

OBJECTIVE: This paper describes an approach for developing intelligent tutoring systems (ITS) for teaching clinical reasoning. MATERIALS AND METHODS: Our approach to ITS for clinical reasoning uses a novel hybrid knowledge representation for the pedagogic model, combining finite state machines to model different phases in the diagnostic process, production rules to model triggering conditions for feedback in different phases, temporal logic to express triggering conditions based upon past states of the student's problem solving trace, and finite state machines to model feedback dialogues between the student and TeachMed. The expert model is represented by an influence diagram capturing the relationship between evidence and hypotheses related to a clinical case. RESULTS: This approach is implemented into TeachMed, a patient simulator we are developing to support clinical reasoning learning for a problem-based learning medical curriculum at our institution; we demonstrate some scenarios of tutoring feedback generated using this approach. CONCLUSION: Each of the knowledge representation formalisms that we use has already been proven successful in different applications of artificial intelligence and software engineering, but their integration into a coherent pedagogic model as we propose is unique. The examples we discuss illustrate the effectiveness of this approach, making it promising for the development of complex ITS, not only for clinical reasoning learning, but potentially for other domains as well.

Computer Simulation↗
PubMed1996

Computer-guided randomized concentration-controlled trials of tacrolimus in autoimmunity: multiple sclerosis and primary biliary cirrhosis.

A randomized concentration-controlled clinical trial (RCCCT) is a trial design in which patients are randomized to predefined blood drug concentrations (low, medium, high). If the concentration ranges are sufficiently separated, this study design can reveal important blood concentration-response relations. Tacrolimus is a potent yet "infant" immunosuppressant for the treatment and prevention of graft rejection and has been shown to exhibit significant clinical activity in some immune-mediated disorders. A tacrolimus artificial intelligence modeling system (AIMS) was used to guide patient dosing to achieve target concentrations specified by the study protocols. In the Multiple Sclerosis study group, we were able to define a concentration range (0.3-0.7 ng/ml) that appeared to show efficacy and minimal tacrolimus toxicity. Patients randomized to the high zone (0.6-1.2 ng/ml) in the Primary Biliary Cirrhosis study group showed significant reduction (approximately 50%) in surrogate efficacy markers [aspartate aminotransferase (SGOT), alanine aminotransferase (SGPT)] compared with patients in the low zone (0.1-0.6 ng/ml). Therefore the RCCCT allowed the detection and delineation of clinically significant concentration-response relations in an ethical and efficient manner.

Artificial Intelligence↗
PubMedDate not supplied

Case studies of laser Doppler imaging system for clinical diagnosis applications and management.

The laser Doppler perfusion imager (LDPI) is a recent development in the field of laser Doppler flowmetry. It has great potential in many medical applications for the non-invasive diagnosis of problems based on microvascular perfusion. Established applications include assessment of breast skin blood flow, wound healing, skin burn, and systemic sclerosis. This paper aims to enhance the usability of LPDI for diagnostics testing through the examination of two major issues. The first issue deals with the performance of the LDPI technique. Two case studies are used not only to highlight the potential applications of LDPI, but also to illustrate the general procedure/precautions needed for ensuring the consistency and quality of the captured perfusion images. The first case study deals with the perfusion across the proximal interphalangeal joints of patients with osteoarthritis. The results showed that LDPI could provide an objective and specific assessment of hyperaemia over the interphalangeal joints in patients with rheumatoid arthritis. The second case study deals with the blood flow on the stomach region during acupuncture. The results indicated that LDPI could provide an objective and specific assessment of the stimulation level on acupuncture point. The issues discussed in these case studies would be useful for the evolution of other novel LDPI applications and the standardization of the proper clinical procedure for the capturing of the LDP images. The second issue deals with the intelligent management of the LDPI results to facilitate the prescription of treatment based on analysis of similar cases previously encountered. The framework of an intelligent diagnostics assistant is proposed to automate the search and retrieval of relevant past cases based on the LDPI diagnosis. The paper uses skin burn as an example to discuss the considerations and techniques for the implementation of the proposed intelligent diagnostics system. This work constitutes initial efforts to increase the productivity of the doctors in diagnostics testing using LDPI.

Abdomen↗
PubMed2004

AutoTutor: a tutor with dialogue in natural language.

AutoTutor is a learning environment that tutors students by holding a conversation in natural language. AutoTutor has been developed for Newtonian qualitative physics and computer literacy. Its design was inspired by explanation-based constructivist theories of learning, intelligent tutoring systems that adaptively respond to student knowledge, and empirical research on dialogue patterns in tutorial discourse. AutoTutor presents challenging problems (formulated as questions) from a curriculum script and then engages in mixed initiative dialogue that guides the student in building an answer. It provides the student with positive, neutral, or negative feedback on the student's typed responses, pumps the student for more information, prompts the student to fill in missing words, gives hints, fills in missing information with assertions, identifies and corrects erroneous ideas, answers the student's questions, and summarizes answers. AutoTutor has produced learning gains of approximately .70 sigma for deep levels of comprehension.

Algorithms↗
PubMed2001

Excellent therapeutic efficacy and minimal late neurotoxicity in children treated with 18 grays of cranial radiation therapy for high-risk acute lymphoblastic leukemia: a 7-year follow-up study of the Dana-Farber Cancer Institute Consortium Protocol 87-01.

BACKGROUND: In the current study, the authors evaluated late neuropsychologic effects 7 years after diagnosis and the long-term survival in a cohort of patients treated for high-risk childhood acute lymphoblastic leukemia (ALL) with cranial radiation therapy. Efficacy and toxicity were evaluated in relation to patient age at diagnosis (age < or > or = 36 months). METHODS: Two hundred and one patients treated for high-risk ALL on the Dana-Farber Cancer Institute Consortium Protocol 87-01 were included, 147 of whom were in continuous complete disease remission and were eligible for cognitive testing. Sixty-one patients consented to undergo testing. All patients received 18 grays (Gy) of cranial radiation as a component of central nervous system treatment. RESULTS: For all 201 patients, the 5-year overall survival (% +/- the standard error) was 82% +/- 2 and the 5-year event-free survival (% +/- the standard error) was 75% +/- 3. Only two patients developed a central nervous system recurrence. Intelligence quotient (IQ) and memory were at the expected mean for age, but performance on a complex figure drawing task was found to be reduced. Children who were age < 36 months at the time of diagnosis were found to have an IQ in the average range, but showed verbal deficits. CONCLUSIONS: The results of the current study demonstrate excellent efficacy of therapy and relatively limited late neurotoxicity on a childhood ALL therapy protocol in which all evaluated patients had received 18 Gy of cranial radiation. Efficacious therapy that includes cranial radiation does not appear to necessarily incur a heightened risk for significant cognitive impairment.

Adolescent↗
PubMed1992

Decision analysis for periodontal therapy.

Current decision-making approaches in clinical medicine and dentistry are based on principles developed when diagnostic and therapeutic options were few. The rapid pace of new technology development and the role of third-party payment systems are increasingly requiring that health-care providers and patients confront very complex decisions. These decisions typically involve significant uncertainty (e.g., How will a specific patient respond to each possible treatment?) and difficult tradeoffs (e.g., How much are patients willing to pay in money, time, and treatment effectiveness to avoid pain and discomfort?). This paper discusses high-quality decision-making. High-quality diagnostic and therapeutic decisions result from a well-developed decision basis that represents the alternatives, information, and preferences pertaining to the decision at hand. An effective decision basis is framed to address patients' and clinicians' key concerns. The resulting recommendation for action is based on an understanding of what factors are most sensitive in determining the best course of action. Moreover, the value of additional information-gathering efforts (e.g., further diagnosis) can be measured before the information is obtained to determine whether it is worth more than it costs. The paper illustrates the need for better decision-making methods with a sample patient case, discusses key decision analysis principles and methods, identifies specific areas where periodontal decision-making can be improved by decision analysis, and presents a periodontal decision analysis case. It then discusses how intelligent decision system technology can make decision analysis widely available in a clinical setting and concludes by exploring how a future dental office might use this technology on a routine basis.

Decision Making↗
PubMed2000

An intelligent diabetes software prototype: predicting blood glucose levels and recommending regimen changes.

Maintaining optimal blood glucose (BG) control is difficult for type 1 diabetes mellitus (T1DM) patients when typical daily regimens of food, insulin and exercise are altered. Artificial intelligence (AI) systems consisting of treatment algorithms calibrated through large datasets of patient specific information may offer a solution. Such a system can predict BG level changes resulting from regimen disturbances and recommend regimen changes for compensation. A software prototype based on neural network, fuzzy logic, and expert system concepts was developed and evaluated to determine feasibility and efficacy of a patient specific prediction model. BG data are the primary driver for adapting existing functions to patient specific prediction algorithms. Mean absolute percent error (MAPE) between actual and predicted BG values from inputs of daily insulin, food, and exercise information for an T1DM test subject was 10.5% using a calibrated model. The prototype is limited by the requirement for a rigid testing schedule, human error and situational circumstances such as alcohol consumption, illness, infection, stress, and significant hormonal imbalances. No significant conclusions regarding model validity can be drawn due to limited evaluation process and subject sample size, although the prototype has demonstrated viability as a learning tool for diabetes patients. Increased impetus for further development of this prototype and similar AI models may materialize when more effective diagnostic and data capture tools become available to reduce testing and improve accuracy of the model with more input data.

Algorithms↗
PubMed2005

Predicting the effect of various ISA penetration grades on pedestrian safety by simulation.

Intelligent speed adaption (ISA) is one type of vehicle-based intelligent transportation systems (ITS), which warns and regulates driving speed according to the speed limits of the roads. Early field studies showed that ISA could reduce general mean speed levels and their variances in different road environments. This paper studies the effects of various ISA penetration grades on pedestrian safety in a single lane road. A microscopic traffic simulation tool, TPMA, was further developed and used to implement different ISA penetration grades. Momentary spot speed and traffic flow data are first logged in the traffic simulation for later prediction of pedestrian safety. Then a hypothetical vehicle-pedestrian collision model is extended from early researches in order to estimate two safety indicators: probability of collision, and risk of death. Finally, Monte Carlo method is applied iteratively to compute those safety indices. The computational result shows that raising ISA penetration in traffic flow will reduce both the probability of mid-block collision between vehicle and pedestrian and the risk of death in the collision accidents. Furthermore, the decrease of the risk of death will be more prominent than that of the collision probability according to this method.

Acceleration↗
PubMed2002

The semantic metadatabase (SEMEDA): ontology based integration of federated molecular biological data sources.

A system for "intelligent" semantic integration and querying of federated databases is being implemented by using three main components: A component which enables SQL access to integrated databases by database federation (MARGBench), an ontology based semantic metadatabase (SEMEDA) and an ontology based query interface (SEMEDA-query). In this publication we explain and demonstrate the principles, architecture and the use of SEMEDA. Since SEMEDA is implemented as 3 tiered web application database providers can enter all relevant semantic and technical information about their databases by themselves via a web browser. SEMEDA' s collaborative ontology editing feature is not restricted to database integration, and might also be useful for ongoing ontology developments, such as the "Gene Ontology" [2]. SEMEDA can be found at http://www-bm.cs.uni-magdeburg.de/semeda/. We explain how this ontologically structured information can be used for semantic database integration. In addition, requirements to ontologies for molecular biological database integration are discussed and relevant existing ontologies are evaluated. We further discuss how ontologies and structured knowledge sources can be used in SEMEDA and whether they can be merged supplemented or updated to meet the requirements for semantic database integration.

Databases, Genetic↗
PubMed1997

[Information model of systemic organization of human mental functions: new approach to the problem of artificial intelligence].

The information model of systemic functions of the human brain reproduces important features of human intelligence: goal planning, prediction of needed results, behavior correction by feedback from the parameters of the results obtained and their comparison with the acceptor of action results. Human behavior imitation in the model is statistically proved by testing the model on a computer. An Adaptron apparatus based on the model quantitatively estimates the parameters of an important mechanism of the brain, namely human intuitive learning. With the Adaptron, the ade-dependent properties and some human intellectual dysfunctions are estimated, which reflect the mechanisms of prediction of future results, the building of memory traces in intuitive learning when the findings coincide with the planned results and the restructure of memory and respective behavior changes when the findings do not coincide with the planned ones.

Artificial Intelligence↗
PubMed1991

The structure of expert diagnostic knowledge in occupational medicine.

Development of an artificial intelligence expert system for diagnosing occupational lung disease requires explicit specification of the structure of knowledge necessary in clinical occupational medicine independent of the process by which the knowledge is utilized. Furthermore, explicit recognition of sources of uncertainty is necessary. Seven categories of knowledge define the diagnostic knowledge base in occupational pulmonary medicine. These include four objects (jobs, industries, exposures, and diseases) and three relationships between pairs of objects. This analysis demonstrates some of the unique aspects of occupational medicine expertise.

Algorithms↗
PubMed1997

Using the Basis of a Knowledge Space for Determining the Fringe of a Knowledge State

Doignon and Falmagne have developed the concept of the fringe of a knowledge state based upon the neighborhood of knowledge states. This concept is useful for probabilistic assessment of knowledge and for the suggestion of training problems in an intelligent tutoring system. In this paper, a generalized definition of the fringe of knowledge states is introduced. An efficient procedure is presented which computes the fringe of knowledge states using the basis of a knowledge space. In a simulation study, this procedure is compared with the approach described by Doignon and Falmagne. Copyright 1997 Academic Press

Journal Article↗
PubMed1995

An approach to intelligent ischaemia monitoring.

The paper describes an approach to intelligent ischaemia event detection based on ECG ST-T segment analysis. ST-T trends are processed by means of a Bayesian forecasting approach using the multistate Kalman filter. A complete procedure, intended for use in CCU/ICU monitoring areas, is proposed, in order to give the clinician an intelligent monitoring tool. The approach serves to describe trends and their changes in a symbolic way. A novel aspect is its ability to observe certain features of ST-T elevation/depression not detected by other means, and to reject artefacts and erroneous events. A sensitivity of 89.58% and a predictivity of 84.31% are obtained on selected records of the European ST-T database. Using a restriction on event amplitude, the predictivity is raised to 95.55%. An ischaemia sensitivity index of 1.2 was determined. The method has been shown to be a robust and practical trend analysis tool, and seems to be appropriate for numeric/symbolic transformations in next-generation intelligent monitoring systems.

Bayes Theorem↗
PubMed1996

Statistical analysis of accident severity on rural freeways.

The growing concern about the possible safety-related impacts of Intelligent Transportation Systems (ITS) has focused attention on the need to develop new statistical approaches to predict accident severity. This paper presents a nested logit formulation as a means for determining accident severity given that an accident has occurred. Four levels of severity are considered: (1) property damage only, (2) possible injury, (3) evident injury, and (4) disabling injury or fatality. Using 5-year accident data from a 61 km section of rural interstate in Washington State (which has been selected as an ITS demonstration site), we estimate a nested logit model of accident severity. The estimation results provide valuable evidence on the effect that environmental conditions, highway design, accident type, driver characteristics and vehicle attributes have on accident severity. Our findings show that the nested logit formulation is a promising approach to evaluate the impact that ITS or other safety-related countermeasures may have on accident severities.

Accidents, Traffic↗
PubMed1990

The structural basis of the mutagenicity of chemicals in Salmonella typhimurium: the National Toxicology Program Data Base.

A portion of the U.S. National Toxicology Program (NTP) Salmonella typhimurium mutagenicity data base was analyzed by CASE, an artificial intelligence SAR system. CASE identified 13 structural determinants which, with a high probability (p less than or equal to 0.05) predicted the likelihood of mutagenicity of the 243 chemicals in the data base (sensitivity = 0.989; specificity = 0.950) as well as of chemicals not included in the data base. CASE also identified an additional set of structures which were highly predictive of mutagenic potency (sensitivity = 0.949; specificity = 1.00). Even though there is little overlap among the chemicals included in the NTP and Gene-Tox Salmonella data bases, CASE found significant similarities between the structural determinants of the mutagenicity in the two data bases, thereby validating the analyses and indicating a commonality in the structural basis of mutagenicity.

Information Systems↗
PubMed1989

Needle aspiration biopsy: past, present, and future.

Since its inception more than 50 years ago at Memorial Hospital for Cancer (New York), needle aspiration biopsy has traveled to its present popularity over a torturous road. The early influence of Stewart on the interpretation of aspiration smears and the use of this biopsy method is still worthy of review, particularly the importance of close cooperation between clinician and pathologist. While cytology has been profoundly influenced by individual cell interpretation as practiced by Papanicolaou, it is really pattern recognition that dominates successful diagnosis by the aspiration biopsy smear method. Present concerns over technical variation in procurement of the biopsy and staining methods should be of less importance than identification of the aspiration methodology that produces the best-quality microscopic image. Reliability of diagnosis by aspiration smear must also be judged by a suitable and reproducible standard, something that is not necessarily fulfilled by tissue pathology, although many would believe otherwise. The author proposes that aspiration may also now be judged, like tissue pathology, by clinical outcome. The application and ease of procuring cell samples from tumors for cell image analysis, for flow cytometry and ploidy studies, and for gene rearrangement place this biopsy method in the forefront of the integration of biologic research and clinical medicine. Aspiration biopsy has caused us to explore how the human eye and brain analyze microscopic images and may even assist in the design of useful artificial intelligence diagnostic systems in the future.

Biopsy, Needle↗
PubMedDate not supplied

Nonconscious intelligence in the universe.

Animals lacking humanoid intelligence have evolved systems indistinguishable in function, if not in structure, from systems built by humans. Although radio communication has never been verified in animals, it is completely feasible biologically. If such systems are present in non-intelligent organisms on other planets, then our chances of detecting life in the universe by current SETI methods are greatly enhanced.

Animal Communication↗