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At least 1,693 records · Page 94Linked to original sources
PubMed2006

Minimum classification error training for online handwriting recognition.

This paper describes an application of the Minimum Classification Error (MCE) criterion to the problem of recognizing online unconstrained-style characters and words. We describe an HMM-based, character and word-level MCE training aimed at minimizing the character or word error rate while enabling flexibility in writing style through the use of multiple allographs per character. Experiments on a writer-independent character recognition task covering alpha-numerical characters and keyboard symbols show that the MCE criterion achieves more than 30 percent character error rate reduction compared to the baseline Maximum Likelihood-based system. Word recognition results, on vocabularies of 5k to 10k, show that MCE training achieves around 17 percent word error rate reduction when compared to the baseline Maximum Likelihood system.

Algorithms↗
PubMed2003

Internet based expert system for the management of gallstones, renal, ureteric and bladder calculi.

An Internet based expert system for the management of gallstones, Renal, Ureteric and bladder calculi based on ultrasound images is presented in this paper. Calculi are due to abnormal collection of certain chemicals like oxalate, phosphate and Uric acid. These calculi can be present in kidney, Ureter or in Urinary bladder and also in gall bladder. The expert system is designed to assist the physician to detect, extract, classify and diagnose calculi with greater accuracy. It also helps physicians in the management of calculi based on the etiological analysis of calculi. The Expert system takes an ultrasound image as input along with the symptoms of the patients. The expert system extracts the renal calculi and analyzes it using different image processing techniques to extract the image features like size, location and texture. These image features along with the clinical data of the patient enable the expert system to provide the decisions to decide the future course of treatment with more accuracy.

Artificial Intelligence↗
PubMed1997

[Computer-assisted smoking cessation].

Though the prevalence of cigarette smoking has declined it still remains the leading cause of premature death from chronic disease. In the prevention of tobacco associated disease the promotion of smoking cessation is a key strategy. This article presents a smoking cessation program based on the transtheoretical model, an empirical model distinguishing five stages of behavioral change. Specific interventions are matched to the current stage of change. Smokers in the intervention program repeatedly fill in questionnaires about their smoking habits, attitudes and strategies in the smoking cessation process. The individual questionnaires are analyzed by a computerized expert system which creates letters with comments on the smoking cessation process and suggestions for further steps from a pool of feedback paragraphs. A further component of the program are five stage-matched brochures. The efficacy of the expert system and its potential impact on Public Health are discussed.

Artificial Intelligence↗
PubMed1977

A communication system for the severely dysarthric speaker with an intact language system.

Two severely dysarthric speakers who had previously spelled entire messages on an alphabet board were taught a system in which they pointed to the first letter of each word as they spoke. Rate and intelligibility of speech produced with (aided) and without (unaided) the communication system were judged by observers who viewed videotaped samples. The rate of aided and unaided speech was markedly faster than spelling the entire message. Aided speech was slower but more intelligible than unaided speech. Further analysis revealed that intelligibility was influenced by at least two factors: (1) rate and (2) information provided by the identification of the first letter of each word. For one speaker both factors contributed to increased intelligibility, while for the other speaker only initial letter information appeared to influence intelligibility.

Audiovisual Aids↗
PubMed2006

The features and shortcomings for gene delivery of current non-viral carriers.

Since the viral vector for gene therapy has serious problems, including oncogenesity and other adverse effects, non-viral carriers have attracted a great deal of attention. Non-viral carriers are expected to achieve gene therapy without serious side effects. However, the most critical issue of gene delivery by non-viral carriers is the low-expression efficiencies of the desired gene. In order to apply non-viral carriers for gene therapy in practical clinical usage, further understanding of the cellular barriers against gene delivery is a prerequisite. Moreover, additional intelligent concepts for gene delivery are also needed. We will summarize the features and shortcomings of currently developed non-viral delivery systems. Especially, we will address the current progress of cationic lipids (lipoplex) and cationic polymers (polyplex) in terms of transfection efficiency. Furthermore, our group has developed a system that responds to the particular intracellular signals of target disease cells. We have named this gene delivery system a drug delivery system based on responses cellular signal (D-RECS). We will introduce this new concept of intelligent non-viral delivery system that our group recently developed.

Animals↗
PubMed1999

Distributing knowledge maintenance for clinical decision-support systems: the "knowledge library" model.

The maintenance of knowledge-rich clinical decision-support systems is challenging, in particular in the complex setting of a large academic medical center. Distributing the maintenance tasks to the source of expertise can address scalability, accuracy and currency issues. It also helps to foster a more global sense of ownership among the system users. The knowledge maintenance model must provide processes and tools to deal with a wide range of stakeholders (resident and attending physicians, consulting specialists, other care providers, case managers, ancillary departments), with knowledge embedded in legacy departmental systems, and with the continuous evolution of the content and form of the knowledge base. We describe and illustrate the "knowledge library" model in use at Vanderbilt University Medical Center for the distributed maintenance of the integrated knowledge base that drives the WizOrder clinical decision-support, physician order entry, and notes capture system.

Artificial Intelligence↗
PubMed1993

Segmental intelligibility and speech interference thresholds of high-quality synthetic speech in presence of noise.

Technological advancement in the area of synthetic speech has made it increasingly difficult to distinguish quality of speech based solely on intelligibility scores obtained in benign laboratory conditions. Intelligibility scores obtained for natural speech and a high-quality text-to-speech system (DECtalk) are not substantially different. This study examined the perceived intelligibility and speech interference thresholds of DECtalk male and female voices and compared them with data obtained for natural speech. Results revealed that decreasing signal-to-noise levels had more deleterious effects on the perception of DECtalk male and female voices than on the perception of natural speech. Analysis of pattern of phoneme errors revealed that similar general patterns of errors tended to occur in DECtalk and in natural speech. The speech interference test did not demonstrate any significant difference between the DECtalk male and female voices. These results were supported by the absence of a significant difference between DECtalk male and female voices during intelligibility testing at different signal-to-noise ratios.

Acoustic Stimulation↗
PubMed1993

Arden Syntax as a standard for knowledge bases in the clinical chemistry laboratory.

Arden Syntax, a standard specification for defining and sharing modular health knowledge bases, is introduced in the clinical chemistry laboratory. A decision support system is constructed and integrated with a laboratory information system for validation of test results with the delta check method. Adopting the Arden Syntax makes it easier to share knowledge bases between laboratories. Tools for handling Arden Syntax knowledge bases and methods for decision support system implementation and integration with a laboratory information system are available today.

Artificial Intelligence↗
PubMed2005

PHSkb: a knowledgebase to support notifiable disease surveillance.

BACKGROUND: Notifiable disease surveillance in the United States is predominantly a passive process that is often limited by poor timeliness and low sensitivity. Interoperable tools are needed that interact more seamlessly with existing clinical and laboratory data to improve notifiable disease surveillance. DESCRIPTION: The Public Health Surveillance Knowledgebase (PHSkb) is a computer database designed to provide quick, easy access to domain knowledge regarding notifiable diseases and conditions in the United States. The database was developed using Protégé ontology and knowledgebase editing software. Data regarding the notifiable disease domain were collected via a comprehensive review of state health department websites and integrated with other information used to support the National Notifiable Diseases Surveillance System (NNDSS). Domain concepts were harmonized, wherever possible, to existing vocabulary standards. The knowledgebase can be used: 1) as the basis for a controlled vocabulary of reportable conditions needed for data aggregation in public health surveillance systems; 2) to provide queriable domain knowledge for public health surveillance partners; 3) to facilitate more automated case detection and surveillance decision support as a reusable component in an architecture for intelligent clinical, laboratory, and public health surveillance information systems. CONCLUSIONS: The PHSkb provides an extensible, interoperable system architecture component to support notifiable disease surveillance. Further development and testing of this resource is needed.

Communicable Diseases↗
PubMed1999

Patient positioning using artificial intelligence neural networks, trained magnetic field sensors and magnetic implants.

The purpose of this study was to evaluate the precision of a sensor and to ascertain the maximum distance between the sensor and the magnet, in a magnetic positioning system for external beam radiotherapy using a trained artificial intelligence neural network for position determination. Magnetic positioning for radiotherapy, previously described by Lennernäs and Nilsson, is a functional technique, but it is time consuming. The sensors are large and the distance between the sensor and the magnetic implant is limited to short distances. This paper presents a new technique for positioning, using an artificial intelligence neural network, which was trained to position the magnetic implant with at least 0.5 mm resolution in X and Y dimensions. The possibility of using the system for determination in the Z dimension, that is the distance between the magnet and the sensor, was also investigated. After training, this system positioned the magnet with a mean error of maximum 0.15 mm in all dimensions and up to 13 mm from the sensor. Of 400 test positions, 8 determinations had an error larger than 0.5 mm, maximum 0.55 mm. A position was determined in approximately 0.01 s.

Humans↗
PubMed2001

Electronic documentation in endoscopy: present status and future perspectives from a company standpoint.

At the beginning of the development of endoscopic information systems all companies were technology-oriented. Today, we see a change from technology to content orientation, the same development which is seen in internet technology. In future systems, it will not be the software that makes a difference but the contents. Contents means not only patient data but also algorithms for feature extraction within large databases with reference images, for example [20]. The automatic recognition of features, such as a complication rate that is too high or a correlation of a certain disease with an endoscopic finding, will be part of a content-based approach. It means that content will also be the knowledge base which has to be developed for future systems. The system of the future will be much more intelligent and less software technology-oriented.

Computer Communication Networks↗
PubMedDate not supplied

Loading a nursing expert system from text: a case study.

A major bottleneck in the construction of expert systems has traditionally been the solicitation and formalization of expertise from the "human expert." As a means of reducing this bottleneck, the authors propose the use of "text" as a source of knowledge. Acquisition of knowledge from text has not been successful thus far, primarily because most text is not presented in a format (rules, frames, or logic) that can be directly used to load a knowledge base. The authors propose techniques to overcome these inherent problems. This article introduces a model for building an expert system that relies on "text" as the source of knowledge. The model is introduced via a case study involving the building of a nurse expert system designed to replicate the medical diagnostic activities of professional nurses.

Artificial Intelligence↗
PubMed2004

The use of computer vision in an intelligent environment to support aging-in-place, safety, and independence in the home.

This paper discusses the use of computer vision in pervasive healthcare systems, specifically in the design of a sensing agent for an intelligent environment that assists older adults with dementia during an activity of daily living. An overview of the techniques applied in this particular example is provided, along with results from preliminary trials completed using the new sensing agent. A discussion of the results obtained to date is presented, including technical and social issues that remain for the advancement and acceptance of this type of technology within pervasive healthcare.

Activities of Daily Living↗
PubMed1988

The relationship between nonverbal intelligence, familial sinistrality and Geschwind scores in right-handed female subjects.

I proposed that there might be a strong relationship between the psychological and motor systems, and argued that hand preference could be related to intelligence; higher IQs are to be expected in right-handers with familial sinistrality (FS) than without FS (Tan, in press). This hypothesis was tested in this work. Cattle's Culture Fair Intelligence Test was used to assess the ability of spatial reasoning in right-handed females. Hand preference was assessed by the Edinburgh Handedness Questionnaire; a laterality score (Geschwind score) was calculated for each subject. The sample from the Nursery High-school had a significantly lower mean IQ than that from the Medical Faculty. The incidence for the consistent right-handers was significantly higher in the sample with lower mean IQ than that with higher mean IQ. The incidence for the weak right-handers was significantly higher in the sample with higher mean IQ than that with lower mean IQ. The incidence for familial sinistrality was significantly higher in the sample with higher mean IQ than that with lower mean IQ. It was concluded that handedness, familial sinistrality, and intelligence are interrelated traits; an attenuation in cerebral asymmetry as a result of an increase in the right hemisphere's mental abilities, reflecting itself in weak right-handedness in conjunction with FS, could be a prerequisite for well-developed nonverbal intelligence.

Adult↗
PubMed2001

Modeling data and knowledge in the EON guideline architecture.

Compared to guideline representation formalisms, data and knowledge modeling for clinical guidelines is a relatively neglected area. Yet it has enormous impact on the format and expressiveness of decision criteria that can be written, on the inferences that can be made from patient data, on the ease with which guidelines can be formalized, and on the method of integrating guideline-based decision-support services into implementation sites' information systems. We clarify the respective roles that data and knowledge modeling play in providing patient-specific decision support based on clinical guidelines. We show, in the context of the EON guideline architecture, how we use the Protégé-2000 knowledge-engineering environment to build (1) a patient-data information model, (2) a medical-specialty model, and (3) a guideline model that formalizes the knowledge needed to generate recommendations regarding clinical decisions and actions. We show how the use of such models allows development of alternative decision-criteria languages and allows systematic mapping of the data required for guideline execution from patient data contained in electronic medical record systems.

Artificial Intelligence↗