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A prototype generalized network technology for hospitals: initial implementation.

A demonstration implementation of a distributed data-processing hospital information system using an intelligent local area communications network (LACN) technology is described. This system is operational at the UCSF Medical Center and integrates four heterogeneous, stand-alone minicomputers. The applications systems are PID/Registration, Outpatient Pharmacy, Clinical Laboratory, and Radiology/Medical Records. Functional autonomy of these systems has been maintained, and no operating system changes have been required. The LACN uses a fiber-optic communications medium and provides extensive communications protocol support within the network, based on the ISO/OSI Model. The architecture is reconfigurable and expandable. This paper describes system architectural issues, the applications environment, and the local area network.

California↗

"Intelligent" polymers in medicine and biotechnology.

One can define "intelligent" polymers as those polymers that respond with large property changes to small physical or chemical stimuli. These polymers may be in various forms, such as in solution, on surfaces, or as solids. One may also combine intelligent aqueous polymer systems with biomolecules to yield a large family of polymers that respond intelligently to physical, chemical, or biological stimuli. This article overviews such interesting and versatile polymer systems.

Biochemical Phenomena↗

Sniffing out the truth: clinical diagnosis using the electronic nose.

Recently the use of smell in clinical diagnosis has been rediscovered due to major advances in odour sensing technology and artificial intelligence (AI). It was well known in the past that a number of infectious or metabolic diseases could liberate specific odours characteristic of the disease stage. Later chromatographic techniques identified an enormous number of volatiles in human clinical specimens that might serve as potential disease markers. "Artificial nose" technology has been employed in several areas of medical diagnosis, including rapid detection of tuberculosis (TB), Helicobacter pylori (HP) and urinary tract infections (UTI). Preliminary results have demonstrated the possibility of identifying and characterising microbial pathogens in clinical specimens. A hybrid intelligent model of four interdependent "tools", odour generation "kits", rapid volatile delivery and recovery systems, consistent low drift sensor performance and a hybrid intelligent system of parallel neural networks (NN) and expert systems, have been applied in gastric, pulmonary and urine diagnosis. Initial clinical tests have shown that it may be possible in the near future to use electronic nose technology not only for the rapid detection of diseases such as peptic ulceration, UTI, and TB but also for the continuous dynamic monitoring of disease stages. Major advances in information and gas sensor technology could enhance the diagnostic power of future bio-electronic noses and facilitate global surveillance models of disease control and management.

Biomarkers↗

Towards knowledge-based systems in clinical practice: development of an integrated clinical information and knowledge management support system.

Given that clinicians presented with identical clinical information will act in different ways, there is a need to introduce into routine clinical practice methods and tools to support the scientific homogeneity and accountability of healthcare decisions and actions. The benefits expected from such action include an overall reduction in cost, improved quality of care, patient and public opinion satisfaction. Computer-based medical data processing has yielded methods and tools for managing the task away from the hospital management level and closer to the desired disease and patient management level. To this end, advanced applications of information and disease process modelling technologies have already demonstrated an ability to significantly augment clinical decision making as a by-product. The wide-spread acceptance of evidence-based medicine as the basis of cost-conscious and concurrently quality-wise accountable clinical practice suffices as evidence supporting this claim. Electronic libraries are one-step towards an online status of this key health-care delivery quality control environment. Nonetheless, to date, the underlying information and knowledge management technologies have failed to be integrated into any form of pragmatic or marketable online and real-time clinical decision making tool. One of the main obstacles that needs to be overcome is the development of systems that treat both information and knowledge as clinical objects with same modelling requirements. This paper describes the development of such a system in the form of an intelligent clinical information management system: a system which at the most fundamental level of clinical decision support facilitates both the organised acquisition of clinical information and knowledge and provides a test-bed for the development and evaluation of knowledge-based decision support functions.

Artificial Intelligence↗

[Targeting of anticancer drug using intelligent polymers].

To fabricate the drug targeting system, it is very effective to combine passive targeting with intelligent polymeric system such as temperature-responsive polymers. We have been studying the passive targeting of anticancer drug bonded with or physically trapped in polymeric micelle derived from poly (ethylene oxide) (PEO) and poly (aspartic acid) block copolymer. On the other hand, Poly(N-isopropylacrylamide) (PIPAAm) is known to be a thermo-responsive polymer which has lower critical solution temperature (LCST, 32 degrees C). PIPAAm shows the reversible phase transition above and below LCST. Attempts to apply thermo-responsive drug carriers were made to enhance the site-specificity of polymeric micelle. Namely, novel type of polymeric micelle were prepared from block copolymers comprising N-isopropylacrylamide (IPAAm)-hydrophobic polymers. This temperature responsive micelles were expected to induce selective accumulation controlled by temperature modulation.

Acrylic Resins↗

Artificial intelligence research in anesthesia and intensive care.

This article describes several research directions exploring the application of artificial intelligence techniques in anesthesia and intensive care. Artificial intelligence can be loosely defined as the discipline of designing computer systems that exhibit "intelligent" behavior. This article first introduces artificial intelligence and computer science research and discusses why medicine has proved to be a challenging domain for applying artificial intelligence techniques. A discussion of the central research themes that arise in medical artificial intelligence, many of which are common to different projects and to different medical settings, is followed by a description of specific research projects that apply artificial intelligence techniques in anesthesiology, ventilatory management, and cardiovascular management. Finally, further comments are made on the current state of the field.

Anesthesia↗

Autoresonant control of nonlinear mode in ultrasonic transducer for machining applications.

Experiments conducted in several countries have shown that the improvement of machining quality can be promoted through conversion of the cutting process into one involving controllable high-frequency vibration at the cutting zone. This is achieved through the generation and maintenance of ultrasonic vibration of the cutting tool to alter the fracture process of work-piece material cutting to one in which loading of the materials at the tool tip is incremental, repetitive and controlled. It was shown that excitation of the high-frequency vibro-impact mode of the tool-workpiece interaction is the most effective way of ultrasonic influence on the dynamic characteristics of machining. The exploitation of this nonlinear mode needs a new method of adaptive control for excitation and stabilisation of ultrasonic vibration known as autoresonance. An approach has been developed to design an autoresonant ultrasonic cutting unit as an oscillating system with an intelligent electronic feedback controlling self-excitation in the entire mechatronic system. The feedback produces the exciting force by means of transformation and amplification of the motion signal. This allows realisation for robust control of fine resonant tuning to bring the nonlinear high Q-factor systems into technological application. The autoresonant control provides the possibility of self-tuning and self-adaptation mechanisms for the system to keep the nonlinear resonant mode of oscillation under unpredictable variation of load, structure and parameters. This allows simple regulation of intensity of the process whilst keeping maximum efficiency at all times. An autoresonant system with supervisory computer control was developed, tested and used for the control of the piezoelectric transducer during ultrasonically assisted cutting. The system has been developed as combined analog-digital, where analog devices process the control signal, and parameters of the devices are controlled digitally by computer. The system was applied for advanced machining of aviation materials.

Journal Article↗

An expert system for the diagnosis of epilepsy: results of a clinical trial.

BACKGROUND: Artificial intelligence is an area where computer systems are used to solve real-life problems that require expert human intelligence. Expert systems serve as an effective alternative to supplement the dearth of human experts in a narrow domain of applications. We developed an expert system named SEIZ using DIAGNOS (an expert system shell for diagnostic applications) for the diagnosis and management of epilepsy. METHODS: A clinical trial was done to test the reliability of SEIZ. The clinical and demographic data from the medical records of 50 patients with epilepsy who attended an epilepsy clinic were provided to the expert system. The system-generated diagnosis was compared with the clinical diagnosis. RESULTS: The seizure types and epileptic syndromes for the 50 patients included generalized -tonic-clonic seizure (14), absence (4), complex partial seizure (18), simple partial seizure (4), juvenile myoclonic epilepsy (5) and other epileptic syndromes (3). There were two cases of hysterical conversion reaction. There was concordance in the diagnosis between the expert system and clinician in 47 cases (94%). The overall sensitivity was 94% and the specificity was 100% for absence, generalized tonic-clonic seizures, simple partial seizures and juvenile myoclonic epilepsy; 94% for complex partial seizures and 98% for hysterical conversion reaction. CONCLUSION: This expert system could generate reliable diagnoses for patients with epilepsy. Such a system may be useful for a doctor in a remote or peripheral area where an expert on epilepsy is not available.

Adult↗

[RGSS-IDJ and its application to cranial computed tomography].

RGSS-IDJ is developed as the Japanese version of Report Generation Support System for Imaging Diagnosis (RGSS-ID), which is a developmental computer system that applies artificial intelligence (AI) methods to a reporting system. Now RGSS-IDJ supports the report generation of cranial computed tomography. A representation scheme called Generalized Finding Representation (GFR) is proposed, to bridge the gap between natural language expressions in the radiographic report and AI methods. GRF for RGSS-IDJ is the same as for RGSS-ID. The basic style for entering the findings on the radiograph is the dialogue system with the routine of query and answering it by selecting items with a mouse. This system encodes the input findings into the network expressions, which are represented as the list form in the LISP computer language. And, it reserves them into the knowledge data base. The content of the report will be able to be utilized for various analyses within AI paradigm. The final radiographic report is made in the natural Japanese language.

Artificial Intelligence↗

Intelligent self-tuning of PID control for the robotic testing system for human musculoskeletal joints test.

In this paper, an intelligent proportional-integral-derivative (PID) control method is introduced to the robotic testing system for the biomechanical study of human musculoskeletal joints. For the testing system, the robot is a highly nonlinear and heavily coupled complicated system, and the human spinal specimen also demonstrates nonlinear property when undergoing testing. Although the conventional PID control approach is extensively used in most industrial control systems, it will break down for nonlinear systems, particularly for complicated systems that have no precise mathematical models. To overcome those difficulties, an intelligent fuzzy PID controller is proposed replacing the widely used conventional PID controllers. The fuzzy PID algorithm is outlined using the fuzzy set theory. The design techniques are developed based on the linguistic phase plane approach. The heuristic rules of syntheses are summarized into a rule-based expert system. Experiments are carried out and the results demonstrate the good performance of the robotic testing system using the proposed control method.

Algorithms↗

Relaxation: molecular and physiological significance.

There appears to be a molecular process for relaxation. Given this, we attempt to demonstrate this phenomenon based on established molecular and physiological processes in light of our current understanding of central and peripheral nervous system mechanisms. Central to our hypothesis is the significance of norepinephrine, nitric oxide, dopamine and morphine signaling both in the central and peripheral nervous system. We find that nitric oxide and morphine control catecholamine processes on many levels, including synthesis, release and actions. We conclude that enough scientific information exists to support these phenotmena as actual physical processes that can be harnessed to provide better patient care.

Central Nervous System↗