Artificial intelligence methods for expert medical consultant systems.
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The support systems for the Emergency Medical Services (EMS) at mass gatherings, such as the local marathon or large international baseball games, are underdeveloped. The purposes of this study were to extend well-developed, triage-based, EMS Personal Digital Assistant (PDA) support systems to cover pre-hospital emergency medical services and onsite evaluation forms for the mass gatherings, and to evaluate users ' perceived ease of use and usefulness of the systems in terms of Davis ' Technology Acceptance Model (TAM). The systems were developed based on an established intelligent triage PDA support system and two other forms the general EMS form from the Taipei EMT and the customer-made Mass Gathering Medical form used by a medical center. Twenty-three nurses and six physicians in the medical center, who had served at mass gatherings, were invited to examine the new systems and answer the TAM questionnaire. The PDA systems were composed of 450 information items within 42 screens in 6 categories. The results supported the potential for using triage-based PDA systems at mass gatherings. Overall, most of the subjects agreed that the systems were easy to use and useful for mass gatherings, and they were willing to accept the systems.
In recent years, medical informatics has become a well-recognized branch of medicine. It is a multidisciplinary science that combines information technology and various specialties of medicine. The impact of medical informatics on medical education is advancing along with the rapid developments in computer science. Departments of medical informatics or similar divisions have appeared in schools of medicine in Taiwan in the past 5 years. At National Taiwan University College of Medicine, we offer curricula in basic computer concepts, network concepts, operating systems, word processing, database and data processing, computer media resources, multimedia computer statistics, intelligent health information systems, medical diagnostic support systems, and electronic medical record systems. Distance learning has also been favorably accepted on this campus. Recently, we proposed the concept of a virtual medical campus, which will break the physical barriers of time and space. We expect this revolution to influence every aspect of medicine, especially medical education.
The practice of medicine is characterized by its great variability and by many rare diseases. When the medical students work in hospital units, they must learn the general medical practice in the care of the patient. The purpose of this work was to present a French multifunction decision aid system using artificial intelligence techniques and Hypercard tools for different modules. Through an ergonomic interface, the system assists the user in the construction of medical observations, suggests diagnostic hypothesis, provides documentation and helps the user perform retrieval tasks. The knowledge comes from senior experts and from the pre-existent and large knowledge database, ADM.
The problems of the systems of controlled (and thus also targeted) transport of the drug into the organism is one of the burning questions of contemporary biogalenics. Various more or less successful solutions were elaborated and applied, beginning with the retardette via the so-called intelligent hydrogels to various automatically controlled implants. Modem microfluidic intelligent biomicrosystems, composed of mutually interconnected microtanks, microjets, micropumps, or microcylinders, are very promising. A natural component of the complex biomicrosystem is a sensory subsystem for the collection of information from the bio-environment and a processor for the control of the process of drug supply to the organism. The present technologies of such Bio-Micro-Electro-Mechanical Systems (BioMEMSs) make it possible to revolutionize drug transport not only by facilitating precise dosing and long-term control of the immediate amount of the supplied drug on the basis of the current condition of the patient, but also to target the drug to the site of its pharmacological effect. Though at present there are still many unsolved problems, transition from laboratory conditions to clinical practice has started, and it is only a matter of five to ten years that intelligent BioMEMSs will gradually become a routinely used dosage microform. The paper briefly surveys the present state and the next development of intelligent systems of drug supply into the body of the patient, termed Intelligent Drug Delivery Systems, Intelligent DDSs, or briefly IDDSs.
The process of discriminating among pathologies involving peripheral blood, bone marrow, and lymph node has traditionally begun with subjective morphological assessment of cellular materials viewed using light microscopy. The subtle visible differences exhibited by some malignant lymphomas and leukemia, however, give rise to a significant number of false negatives during microscopic evaluation by medical technologists. We have developed a distributed, clinical decision support prototype for distinguishing among hematologic malignancies. The system consists of two major components, a distributed telemicroscopy system and an intelligent image repository. The hybrid system enables individuals located at disparate clinical and research sites to engage in interactive consultation and to obtain computer-assisted decision support. Software, written in JAVA, allows primary users to control the specimen stage, objective lens, light levels, and focus of a robotic microscope remotely while a digital representation of the specimen is continuously broadcast to all session participants. Primary user status can be passed as a token. The system features shared graphical pointers, text messaging capability, and automated database management. Search engines for the database allow one to automatically identify and retrieve images, diagnoses, and correlated clinical data of cases from a "gold standard" database which exhibit spectral and spatial profiles which are most similar to a given query image. The system suggests the most likely diagnosis based on majority logic of the retrieved cases. The system was used to discriminate among three lymphoproliferative disorders and healthy cells. The system provided the correct classification in more than 83% of the cases studied. System performance was evaluated using rigorous statistical assessment and by comparison with human observers.
A program which utilizes the techniques of Artificial Intelligence and Expert Systems to solve problems in the area of Conformational Analysis is described. The program searches conformational space in a systematic fashion, based on the technique known as heuristic state-space search. The program proceeds by recognizing conformational units, assigning one or more conformational templates to each unit, and joining them to form conformational suggestions. These suggestions are criticized to discover logical inconsistencies, and any resulting stresses are resolved. The resulting conformational suggestions are sometimes accurate enough for immediate use, or may be further refined by a numerical program. The latter combination is shown to be quite efficient compared to purely numerical conformational search techniques.
While medical expert systems helped demonstrate that artificial intelligence was possible, few medical systems have been heralded as practical successes. We believe that expert systems will be practical successes if they cost effectively handle most of a physician's workload (i.e., routine care). To accomplish this goal, technology must appear invisible to the user; the system must be intuitive and anticipate users' needs. "Epileptologists' Assistant" is an example of our approach of combining a graphical user interface with an expert system and data base in a system to help in a routine specialty clinic. The goal is for two nurses and a physician to handle the workload of three physicians while increasing the quality of care. The current system reduces physician time by 66%. Our ultimate goal is to create a unified family of systems for medical specialties.
BACKGROUND: Military aviator helmet communications systems are designed to enhance speech intelligibility (SI) in background noise and reduce exposure to harmful levels of noise. Some aviators, over the course of their aviation career, develop noise-induced hearing loss that may affect their ability to perform required tasks. New technology can improve SI in noise for aviators with normal hearing as well as those with hearing loss. METHODS: SI in noise scores were obtained from 40 rotary-wing aviators (20 with normal hearing and 20 with hearing-loss waivers). There were three communications systems evaluated: a standard SPH-4B, an SPH-4B aviator helmet modified with communications earplug (CEP), and an SPH-4B modified with active noise reduction (ANR). RESULTS: Subjects' SI was better in noise with newer technologies than with the standard issue aviator helmet. A significant number of aviators on waivers for hearing loss performed within the range of their normal hearing counterparts when wearing the newer technology. The rank order of perceived speech clarity was 1) CEP, 2) ANR, and 3) unmodified SPH-4B. CONCLUSIONS: To insure optimum SI in noise for rotary-wing aviators, consideration should be given to retrofitting existing aviator helmets with new technology, and incorporating such advances in communication systems of the future. Review of standards for determining fitness to fly is needed.
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During the last few years intelligent machines appeared in nearly all technical areas, such as consumer electronics, robotics, and industrial control systems. There are for example washing machines that work very effectively, need comparably less power than in the past, and have short execution times because they adjust their washing cycles to each set of clothes and change their washing strategies as the clothes become clean. These intelligent systems are based on fuzzy control strategies, i.e., common sense rules are used to describe a system's behavior instead of complex mathematical models. We have applied this new technology to control problems as well as to reasoning problems in biomedical engineering where appropriate mathematical models could not be built due to the complexity of the problem. After a short introduction to the concepts of fuzzy logic two approaches in the field are described: a fuzzy control strategy for the pump rate adjustment of a novel total artificial heart and an intelligent alarm system based on fuzzy inference which supports the anesthetist in monitoring and evaluating the hemodynamic state of a patient undergoing cardiac surgery. These examples indicate the inherent reliability and stability of this technique in the field of complex dynamic systems. Such properties are highly significant especially in medical applications.
Many professions including medicine have standard operating procedures for the performance of their tasks. In the construction of expert systems, knowledge engineers have exploited this fact in devising heuristic rules that mimic the standard practice among such personnel (i.e., experts). This article suggests that the expert system designer should not stop at the level of the standard operating procedure heuristic but should instead investigate the reasons that the standard procedures have become standard. Because the experts in a field often do not understand the reasons for the standard operating procedures of their profession, this effort not only rewards the system designer but the expert as well. Because medical training does not always emphasize the logical reasoning underlying certain standard operating procedures, the ability to perform this reasoning is especially important in medicine. Further, a medical expert system for consultation or education would make a valuable impact by incorporating such knowledge and inference rules. This article investigates the development of a computerized medical expert system that applies the principles of artificial intelligence by limiting the number of questions and tests to find the solution for an ill-defined complex problem. Finally, we describe a logic program that tests the basic ideas.
In this paper, after reviewing the main issue in artificial intelligence, decision support systems, medical decision-making, expert systems and some of their applications in medicine, we focus on the diagnostic aspect of pancreatic cancer. We briefly examine the most significant applications both from the oncological and from the diagnostic point of view. We discuss the medical problems mentioning incidence and mortality, aetiological factors and diagnosis, considering the roles of surgery and adjuvant therapies. Finally we justify the decision to develop an expert system in such a medical domain and discuss the SPES (Surgical Pancreatic Expert System) project, its parts dealing with the different medical phases of pancreatic cancer diagnosis and therapy: pre-operative, intra-operative and adjuvant therapies. In particular we discuss diagnostic aspects of pancreatic cancer disease, pointing out the aims of the project, methodologies, tools used and future developments.
The support systems for the Emergency Medical Services (EMS) in the mass gatherings, such as the local marathon or the large international baseball games, had been underdeveloped. The purposes for this study were to develop triage-based EMS Personal Digital Assistant (PDA) support systems for the mass-gatherings and to evaluate users' perceived ease of use and usefulness of the systems in terms of Davis' Technology Acceptance Model (TAM). The systems were developed based on an established intelligent triage PDA support system and two other forms-the general EMS form from the Taipei EMT and the customer-made Mass Gathering Medical form used by a medical center. 23 nurses and 6 physicians in the medical center, who had ever served in the mass gatherings, were invited to examine the new systems and answered the TAM questionnaire. The results showed that the PDA systems included as many 450 information items inside 42 screens under 6 categories and the great potential of using triage-based PDA systems in the mass gatherings. Overall, most of the subjects agreed with that the systems were easy to use and useful for the mass gatherings, and they were willing to accept the systems.
Natural human languages have proven to be sub-optimal in artificial intelligence applications because of their tendency to inexact representation of meaning. The author has devised a technique for converting human language to and from a compact byte-coded intermediate representation, which is processed more easily by computer systems. A specialized lexical engine based on IEEE Standard 1275-1994 was created to embed redundant information invisibly within the byte-coded text stream, to enable use of a variety of alphabets, grammars, and pronunciation rules (including slang and regional dialects). Very large vocabularies in a variety of human languages are supported. These lexical tools are designed to facilitate speech recognition and speech synthesis subsystems, universal translators and machine intelligence systems.
The intelligent controlled drug delivery systems are a series of the preparations including microcapsules or nanocapsules composed of intelligent polymers and medication. The properties of preparations can change with the external stimuli such as pH value, temperature, chemical substance, light, electricity and magnetism. According to this properties, the drug delivery can be intelligently controlled. This paper has reviewed research on syntheses and applications of intelligent controlled drug delivery systems with polymers.
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An on-line fault detection and isolation technique is proposed for the diagnosis of rotating machinery. The architecture of the system consists of a feature generation module and a fault inference module. Lateral vibration data are used for calculating the system features. Both continuous-time and discrete-time parameter estimation algorithms are employed for generating the features. A neural fuzzy network is exploited for intelligent inference of faults based on the extracted features. The proposed method is implemented on a digital signal processor. Experiments carried out for a rotor kit and a centrifugal fan indicate the potential of the proposed techniques in predictive maintenance.