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At least 955 records · Page 53Linked to original sources
PubMed1998

Galen-In-Use: using artificial intelligence terminology tools to improve the linguistic coherence of a national coding system for surgical procedures.

GALEN has developed a language independent common reference model based on a medically oriented ontology and practical tools and techniques for managing healthcare terminology including natural language processing. GALEN-IN-USE is the current phase which applied the modelling and the tools to the development or the updating of coding systems for surgical procedures in different national coding centers co-operating within the European Federation of Coding Centre (EFCC) to create a language independent knowledge repository for multicultural Europe. We used an integrated set of artificial intelligence terminology tools named CLAssification Manager workbench to process French professional medical language rubrics into intermediate dissections and to the Grail reference ontology model representation. From this language independent concept model representation we generate controlled French natural language. The French national coding centre is then able to retrieve the initial professional rubrics with different categories of concepts, to compare the professional language proposed by expert clinicians to the French generated controlled vocabulary and to finalize the linguistic labels of the coding system in relation with the meanings of the conceptual system structure.

Artificial Intelligence↗
PubMed1996

VLSI neural system architecture for finite ring recursive reduction.

The use of neural-like networks to implement finite ring computations has been presented in a previous paper. This paper develops efficient VLSI neural system architecture for the finite ring recursive reduction (FRRR), including module reduction, MSB carry iteration and feedforward processing. These techniques deal with the basic principles involved in constructing a FRRR, and their implementations are efficiently matched to the VLSI medium. Compared with the other structure models for finite ring computation (e.g. modification of binary arithmetic logic and bit-steered ROM's), the FRRR structure has the lowest area complexity in silicon while maintaining a high throughput rate. Examples of several implementations are used to illustrate the effectiveness of the FRRR architecture.

Algorithms↗
PubMed2000

A fuzzy-neural system for identification of species-specific alarm calls of Gunnison's prairie dogs.

In this study we describe the design and application of an automated classification system that utilizes artificial intelligence to corroborate the finding that Gunnison's prairie dogs have different alarm calls for different species of predators. This corroboration is strong because it utilizes an entirely different analysis technique than that used in the original research by Slobodchikoff et al. [Slobodchikoff, C.N., Fischer, C., Shapiro, J., 1986. Predator-specific alarm calls of prairie dogs. Am. Zool. 26, 557] or in subsequent study done by Slobodchikoff et al. [Slobodchikoff, C.N., Kiriazis, J., Fischer, C., Creef, E., 1991. Semantic information distinguishing individual predators in the alarm calls of Gunnison's prairie dogs. Anim. Behav. 42, 713-719]. The study described here also is more completely automated than earlier study in this area. This automation allowed a large volume of field data to be processed where all measurements of relevant parameters were performed through software control. Previous study processed a smaller data set and utilized manual measurement techniques. The new classification system, which combines fuzzy logic and an artificial neural network, classified alarm calls correctly according to the eliciting predator species, achieving accuracy levels ranging from 78.6 to 96.3% on raw field data digitized with low quality audio equipment.

Journal Article↗
PubMed1995

A rational reconstruction of INTERNIST-I using PROTEGE-II.

PROTEGE-II is a methodology and a suite of tools that allow developers to build and maintain knowledge-based systems in a principled manner. We used PROTEGE-II to reconstruct the well-known INTERNIST-I system, demonstrating the role of a domain ontology (a framework for specification of a model of an application area), a reusable problem-solving method, and declarative mapping relations in creating a new, working program. PROTEGE-II generates automatically a domain-specific knowledge-acquisition tool, which, in the case of the INTERNIST-I reconstruction, has much of the functionality of the QMR-KAT knowledge-acquisition tool. This study provides a means to understand better both the PROTEGE-II methodology and the models that underlie INTERNIST-I.

Artificial Intelligence↗
PubMed2005

Mobile tele-echography: user interface design.

Ultrasound imaging allows the evaluation of the degree of emergency of a patient. However, in some instances, a well-trained sonographer is unavailable to perform such echography. To cope with this issue, the Mobile Tele-Echography Using an Ultralight Robot (OTELO) project aims to develop a fully integrated end-to-end mobile tele-echography system using an ultralight remote-controlled robot for population groups that are not served locally by medical experts. This paper focuses on the user interface of the OTELO system, consisting of the following parts: an ultrasound video transmission system providing real-time images of the scanned area, an audio/video conference to communicate with the paramedical assistant and with the patient, and a virtual-reality environment, providing visual and haptic feedback to the expert, while capturing the expert's hand movements. These movements are reproduced by the robot at the patient site while holding the ultrasound probe against the patient skin. In addition, the user interface includes an image processing facility for enhancing the received images and the possibility to include them into a database.

Algorithms↗
PubMed2005

Real-time classification of ECGs on a PDA.

The new advances in sensor technology, personal digital assistants (PDAs), and wireless communications favor the development of a new type of monitoring system that can provide patients with assistance anywhere and at any time. Of particular interest are the monitoring systems designed for people that suffer from heart arrhythmias, due to the increasing number of people with cardiovascular diseases. PDAs can play a very important role in these kinds of systems because they are portable devices that can execute more and more complex tasks. The main questions answered in this paper are whether PDAs can perform a complete electrocardiogram beat and rhythm classifier, if the classifier has a good accuracy, and if they can do it in real time. In order to answer these questions, in this paper, we show the steps that we have followed to build the algorithm that classifies beats and rhythms, and the obtained results, which show a competitive accuracy. Moreover, we also show the feasibility of incorporating the built algorithm into the PDA.

Algorithms↗
PubMed1999

Just a beta....

Traditional implementation of clinical information systems follows a predictable project management process. The selection, development, implementation, and evaluation of the system and the project management aspects of those phases require considerable time and effort. The purpose of this paper is to describe the beta site implementation of a knowledge-based clinical information system in a specialty area of a southeastern hospital that followed a less than traditional approach to implementation. Highlighted are brief descriptions of the hospital's traditional process, the nontraditional process, and key findings from the experience. Preliminary analysis suggests that selection of an implementation process is contextual. Selection of elements from each of these methods may provide a more useful process. The non-traditional process approached the elements of communication, areas of responsibility, training, follow-up and leadership differently. These elements are common to both processes and provide a focal point for future research.

Artificial Intelligence↗
PubMed1993

[General aspects of the diagnostic process in acute organic psychoses].

Following the Central European tradition of the triad system of psychiatry of Kurt Schneider (I. Abnormal Reactions/Personalities, II. Acute/Chronic Organic Psychosis, III. Schizophrenia/Cyclothymia) (19) a series of 210 cases of acute organic psychoses was collected. In contrast to DSM-III and in accord with W.A. Lishman (10), this series comprises not only delirium, but the entire range of impairments of consciousness from the "Durchgangssyndrom" of H.H. Wieck (24) to clouding of consciousness and coma, twilight states or apallic syndromes. From this series we present some elementary quantitative data concerning the age distribution of different etiologies, that are generally considered helpful in the diagnostic process. In contrast to this opinion, a single case of bromazepam-induced delirium shows: The anamnesis may be misleading, the general and neurological examination as well as the radiological, laboratory and electrophysiological tests could be insignificant. The essential diagnostic tool is the descriptive or phenomenological psychopathological observation. Compared to it, the general data of the age distribution of different etiologies of organic psychoses are of comparably little help in making a diagnosis. Artificial intelligence and medical expert systems are set out to replace the diagnosis of the physician. Eliminative materialistic neuroscience is set out to replace old-fashioned descriptive psychopathology by quantitative electrical and chemical data. Through the method of systematically confronting general quantitative data with suitably chosen single cases it should be possible to find out essential differences between general reductionist statements and the properties of complex qualitative phenomena like the individual human mind.

Adolescent↗
PubMed2000

DATA: a decision aid for management of the patient with stable angina pectoris.

OBJECTIVE: The patient with stable disabling angina must choose between bypass surgery, coronary angioplasty, or medical therapy. Estimation of comparative outcomes of these alternative therapies is difficult. DESIGN: Utilizing Artificial Intelligence, an expert-system computerized decision aid, DATA (Decision Aid for Therapy of Angina), was developed to run on a personal computer and to calculate the probability of each possible clinical event based on individual patient characteristics. For each therapeutic option, relative clinical outcomes and anticipated charges are computed. Ten patients were evaluated retrospectively by DATA and by a group of cardiologists. RESULTS: DATA agreed with the primary therapy given to all patients. The physician group underestimated the value of alternative therapies and underestimated charges for all therapies. CONCLUSIONS: This decision aid allows comparison of alternative therapies in terms of relative patient outcome and anticipated costs can be better estimated.

Angina Pectoris↗
PubMed1990

Combining statistical, rule-based, and physiologic model-based methods to assist in the management of diabetes mellitus.

Self-monitoring of capillary blood glucose is used by most patients with insulin-dependent diabetes mellitus as a means of assessing metabolic control. Therapeutic interventions are based on retrospective analysis of glycemic response to various factors, with insulin and diet playing the key roles. We describe a computer system being developed for intelligent automated analysis and interpretation of data relevant to glycemic control. CADMO (Computer-Assisted Diabetes Monitor) is intended to assist health care professionals with the management of patients with insulin-dependent diabetes. It takes as input glucose values and insulin doses collected via a memory meter by the patient over a period of several weeks. Rule-based logic, statistical methods, and a physiologic model of insulin pharmacokinetics and glucose dynamics are used to help detect meaningful patterns and trends in glucose and insulin data and to suggest approaches for optimizing insulin regimens.

Blood Glucose↗
PubMed1998

Clinical data entry.

Routine capture of patient data for a computer-based patient record system remains a subject of study. Time constraints that require fast data entry and maximal expression power are in favor of free text data entry. However, using patient data directly for decision support systems, for quality assessment, etc. requires structured data entry, which appears to be more tedious and time consuming. In this paper, a prototype clinical data entry application is described that combines free text and structured data entry in one single application and allows clinicians to smoothly switch between these two different input styles. A knowledge base involving a semantic network of clinical data entry terms and their properties and relationships is used by this application to support structured data entry. From structured data, sentences are generated and shown in a text processor together with the free text. This presentation metaphor allows for easy integrated presentation of structured data and free text.

Artificial Intelligence↗
PubMed2005

High-resolution real-time spiral MRI for guiding vascular interventions in a rabbit model at 1.5 T.

PURPOSE: To study the feasibility of a combined high spatial and temporal resolution real-time spiral MRI sequence for guiding coronary-sized vascular interventions. MATERIALS AND METHODS: Eight New Zealand White rabbits (four normal and four with a surgically-created stenosis in the abdominal aorta) were studied. A real-time interactive spiral MRI sequence combining 1.1 x 1.1 mm(2) in-plane resolution and 189-msec total image acquisition time was used to image all phases of an interventional procedure (i.e., guidewire placement, balloon angioplasty, and stenting) in the rabbit aorta using coronary-sized devices on a 1.5 T MRI system. RESULTS: Real-time spiral MRI identified all rabbit aortic stenoses and provided high-temporal-resolution visualization of guide-wires crossing the stenoses in all animals. Angioplasty balloon dilatation and deployment of coronary-sized copper stents in the rabbit aorta were also successfully imaged by real-time spiral MRI. CONCLUSION: Combining high spatial and temporal resolution with spiral MRI allows real-time MR-guided vascular intervention using coronary-sized devices in a rabbit model. This is a promising approach for guiding coronary interventions.

Animals↗
PubMed2003

Ambient intelligence in health care.

Ambient Intelligence (AmI) is a new paradigm in information technology, in which people are empowered through a digital environment that is aware of their presence and context, and is sensitive, adaptive, and responsive to their needs, habits, gestures and emotions. The most ambitious expression of AmI is Intelligent Mixed Reality (IMR), an evolution of traditional virtual reality environments. Using IMR, it is possible to integrate computer interfaces into the real environment, so that the user can interact with other individuals and with the environment itself in the most natural and intuitive way. How does the emergence of the AmI paradigm influence the future of health care? Using a scenario-based approach, this paper outlines the possible role of AmI in health care by focusing on both its technological and relational nature. In this sense, clinicians and health care providers that want to exploit AmI potential need a significant attention to technology, ergonomics, project management, human factors and organizational changes in the structure of the relevant health service.

Electronics↗
PubMed2005

An automated method for analysis of flow characteristics of circulating particles from in vivo video microscopy.

The behavior of white and red blood cells, platelets, and circulating injected particles is one of the most studied areas of physiology. Most methods used to analyze the circulatory patterns of cells are time consuming. We describe a system named CellTrack, designed for fully automated tracking of circulating cells and micro-particles and retrieval of their behavioral characteristics. The task of automated blood cell tracking in vessels from in vivo video is particularly challenging because of the blood cells' nonrigid shapes, the instability inherent in in vivo videos, the abundance of moving objects and their frequent superposition. To tackle this, the CellTrack system operates on two levels: first, a global processing module extracts vessel borders and center lines based on color and temporal patterns. This enables the computation of the approximate direction of the blood flow in each vessel. Second, a local processing module extracts the locations and velocities of circulating cells. This is performed by artificial neural network classifiers that are designed to detect specific types of blood cells and micro-particles. The motion correspondence problem is then resolved by a novel algorithm that incorporates both the local and the global information. The system has been tested on a series of in vivo color video recordings of rat mesentery. Our results show that the synergy between the global and local information enables CellTrack to overcome many of the difficulties inherent in tracking methods that rely solely on local information. A comparison was made between manual measurements and the automatically extracted measurements of leukocytes and fluorescent microspheres circulatory velocities. This comparison revealed an accuracy of 97%. CellTrack also enabled a much larger volume of sampling in a fraction of time compared to the manual measurements. All these results suggest that our method can in fact constitute a reliable replacement for manual extraction of blood flow characteristics from in vivo videos.

Algorithms↗
PubMed1993

Automatic knowledge acquisition from MEDLINE.

Construction of medical knowledge bases for use in expert systems is an arduous task. We propose a procedure for obtaining medical knowledge via automated analysis of citations found in the National Library of Medicine's MEDLINE database. In this method, simple pattern of keywords and subheading co-occurrences are detected in the keyword descriptor portion of the citations. Each pattern corresponds to a fact, expressed as a semantic relationship between medical concepts. We have constructed a set of 504 pattern-matching rules and applied it to a set of 673 MEDLINE citations to produce 2,795 such facts. The results are presented of an analysis of the syntactic and semantic features of these facts to understand the kinds of knowledge than can be obtained through our method and speculate on the potential uses and pitfalls for knowledge of this type.

Artificial Intelligence↗
PubMed2006

Automated on-the-fly detection and correction procedure for EPR imaging data acquisition.

Fast and reliable data acquisition is a major requirement for successful and useful biological electron paramagnetic resonance imaging (EPRI) experiments. Even a technologically advanced and professionally supervised EPRI system can exhibit instabilities initiated by perturbations such as animal motion, microphonics, and temperature changes. As a result, part of an acquired data set may become corrupted with excessive noise and distortions, which in turn may degrade the quality of the reconstructed image. In this work an automated scheme to monitor the system performance and stability over the course of an experiment is demonstrated. This method ensures that the quality of the acquired data is maintained during the experiment. For this purpose, four parameters including noise content and integration of each acquired projection are quantified and measured against those of the zero-gradient (ZG) projection, which is set as a quality benchmark. Projections with parameter values that differ substantially from the expected values are identified as damaged and consequently are reacquired. Therefore, the proposed technique not only effectively monitors the quality of acquisition, it also saves a substantial amount of acquisition time because it eliminates the necessity of repeating the entire experiment in cases in which only a small fraction of the data are corrupted.

Algorithms↗
PubMed2006

Neuronal plasticity in memory and learning abilities: theoretical position and selective review.

Neural plasticity of modality-nonspecific and modality-specific memory and learning abilities pertains to fluid intelligence and crystallized intelligence, respectively. The limbic system with the novelty neurons of the hippocampus interacts with the prefrontal cortex optimization of the orienting reflex and voluntary attention. Brain-derived neurotrophic factor produced by novelty neurons of the hippocampus contributes to long-term memory formation and improves learning abilities in a wide range of disciplines. Synergistic combination of stimulation with "analytical-specific visual perceptual patterns" and "optimally high" physiological activation of the bilateral electrodermal system optimizes the limbic system and prefrontal cortex activity as demonstrated by enhanced prefrontal N450 ERPs to a memory workload paradigm. This is accompanied by improvements in auditory retention tasks, word memorization, higher school achievement and marks, and an amelioration of "analytical-specific perceptual skills" as measured by the Mangina-Test. Intracerebral ERPs to a memory workload paradigm contributed to the elucidation of limbic structures and neocortical sites involved in memory workload processes. The progressive degeneration of these same structures causes the gradual decline of memory functions observed in early Alzheimer's disease. Research findings indicate that ERPs elicited by a memory workload paradigm are sensitive markers for diagnosis, treatment and clinical follow-up of early Alzheimer's patients. In addition, ERPs provide objective measurement of cholinergic medication effects on cerebral functions involved in memory processes through neuropsychophysiological parameters.

Animals↗
PubMed2026

Effectiveness and usability of artificial intelligence-powered assistive technologies in Supporting daily activities of children with cerebral palsy: a systematic review.

BACKGROUND: Cerebral Palsy (CP) is the main cause of motor disabilities in childhood, necessitating innovative approaches to rehabilitation and assistive technology (AT). Simultaneously, artificial intelligence (AI) is increasingly being integrated into devices to create more adaptive, personalized, and effective AT. This systematic review aimed to evaluate the effectiveness and usability of AI-powered assistive technologies designed to support daily activities and rehabilitation in children with CP. MATERIALS AND METHODS: Five databases, including Scopus, Web of Science, PubMed, Embase, and IEEE Xplore, were systematically searched, and 23 articles were included in the final analysis. Articles were identified, selected, and categorized into emerging thematic areas based on the primary function and application of the technology. RESULTS: Five key thematic topics were identified: 1) AI-driven motor rehabilitation and gait training for functional mobility; 2) intelligent assessment and monitoring systems for clinical decision support; 3) AI-supported communication, social interaction, and intention recognition tools; 4) gamified and virtual reality-based interventions to enhance engagement and usability; and 5) smart assistive systems supporting daily living and independent mobility. The findings demonstrate a strong trend toward the application of AI technologies in personalized, engaging, and data-driven interventions for children with CP. However, the field is predominantly in the proof-of-concept stage, with limitations including small sample sizes, lack of long-term clinical validation, challenges in user-centered design, and usability for children with CP. CONCLUSION: AI-powered assistive technologies hold significant potential for transforming the care of children with CP by enabling highly personalized and engaging interventions. To actualize this potential, future work must realize that practical application remains challenging owing to limited clinical validation, technological integration, and usability barriers for children with CP. Future research must prioritize user-centered design and multidisciplinary collaboration to ensure that AI and robotic advancements improve the usability and quality of life for children with CP.

Humans↗