Expert systems in histopathology. II. Knowledge representation and rule-based systems

Two aspects of expert systems for use in diagnostic histopathology and cytopathology are examined: knowledge representation and the structure and operation of rule-based systems. Knowledge may be represented, e.g., in semantic networks, frames, multiple contexts and model-based structures; the choice of structure should be matched to the type of information to create an efficient and logically adequate expert system. In a rule-based system, knowledge is represented as "rules," often in the form of "IF (condition)-THEN (conclusion)" rules. The anatomy of such rules and their operation is explored via the use of examples. Uncertainty in rules is briefly addressed, and their processing by the symbolic reasoning of the "inference engine" of the expert system is described, including both "forward-chaining" ("data-driven") operations and "backward-chaining" ("goal-driven") operations.     

Expert systems in treating substance abuse.

Computer programs can assist humans in solving complex problems that cannot be solved by traditional computational techniques using mathematic formulas. These programs, or "expert systems," are commonly used in finance, engineering, and computer design. Although not routinely used in medicine at present, medical expert systems have been developed to assist physicians in solving many kinds of medical problems that traditionally require consultation from a physician specialist. No expert systems are available specifically for drug abuse treatment, but at least one is under development. Where access to a physician specialist in substance abuse is not available for consultation, this expert system will extend specialized substance abuse treatment expertise to nonspecialists. Medical expert systems are a developing technologic tool that can assist physicians in practicing better medicine.     

集成的专家系统和神经网络应用于大熊猫生境评价

充分了解大熊猫生境的时空格局及其变化,对有效保护大熊猫非常重要.绘制生境图既是野生动物生境评价和监测的一个有效方式,也是一个必要的步骤.新发展起来的人工智能方法(包括专家系统和神经网络方法),在模拟复杂系统过程中能够同时综合定性和定量信息,并可集成于GIS中,有助于大熊猫复杂生境的制图及评价.为了对大熊猫生境进行评价,本文建立了一个较全面的综合制图方法,将专家系统、神经网络和多类型数据全部集成在GIS环境下.结果表明,采用专家系统和神经网络集成方法绘制的大熊猫生境图的精度达到80％以上,高于单一的专家系统方法、神经网络方法和传统的最大似然法制图的精度.Z统计方法也证实了新建立的专家系统和神经网络集成方法要显著好于3种单一方法.     

Machine learning in quantitative histopathology

The role of expert systems functioning as process controllers in learning image understanding systems is discussed. Numeric learning systems already have found a number of applications in cytologic and histopathologic diagnosis. Depending on the required capabilities, systems of increasing complexity are needed. Expert systems to guide scene segmentation in histopathologic imagery require model-based reasoning. Diagnostic image interpretation with learning capability demands a full model of the human expert's competence, including a considerable variety of knowledge representation schemes and inference strategies, coordinated by a meta-process controller.     

Expert systems in the control of animal cell culture processes: Potentials,functions, and perspectives

In recent years, the development of advanced systems for bioprocess monitoring and control has become an area of intensive research. Along with traditional techniques, there are several new approaches which are increasingly being applied to bioprocess operations. Among these, of special note is expert system technology, which provides possibilities for the design of efficient bioprocess control systems with new functional capabilities. This technology has been successfully applied to variety of microbial processes at laboratory and industrial scale. The present paper analyzes the possibility for application of expert systems to animal cell cultures processes whose high complexity is well suited to expert control. The discussion focuses on the organization and the functionality of the intelligent control systems, and covers some practical aspects of their design.     

Expert systems in histopathology. IV. The management of uncertainty.

Expert systems deal with data that are categorical and conceptual, that represent elements of fuzzy sets and that often, by themselves, do not allow an unequivocal decision. The management of uncertainty in expert systems thus becomes a crucial issue. It involves defining measures of uncertainty and procedures for combining accumulating evidence in a manner that properly considers the dependence structure of diagnostic clues. Probability theory offers valuable procedures for uncertainty assessment; however, their practical application in the domain of quantitative histopathology and histopathologic diagnosis can be problematic.     

Colonic lesion expert system. Performance evaluation

A computer-based expert system for diagnosing colonic sections as normal, adenoma or adenocarcinoma is described, along with an evaluation of its performance. On the basis of its knowledge base, consisting of the values of diagnostic clues and their associated certainty factors for the possible diagnoses, the system will suggest the diagnosis for new cases presented to it. Using the data provided for 16 diagnostic clues, the system arrived at correct diagnoses for all cases of normal colon, for 49 of 50 cases of adenoma and for 48 of 49 cases of adenocarcinoma. Sample outputs from the expert system are presented and discussed, and the effects of possible alterations in the data base are considered.     

Expertise in expert systems: knowledge acquisition for biological expert systems

In this paper it is argued that an expert system requires morethan factual knowledge before it can display expertise in agiven domain. The additional knowledge consists of the heuristicsor ‘rules of thumb’ used by an expert to manipulateand interpret the factual knowledge. The knowledge acquisitionphase of an expert system project involves determining the factualknowledge (which may be obtained from published sources) andthe heuristics used by an expert to manipulate that knowledge-theseheuristics can only be obtained from an expert. In reviewingexisting biological expert systems it is apparent that manycontain only the factual knowledge relating to the domain, andlack the heuristics that enable such systems to show expertise.This paper reviews a number of knowledge acquisition techniqueswhich could be used for acquiring heuristic knowledge and discusseswhen their use is appropriate. The knowledge acquisition techniquesdiscussed are those suitable for the development of small-scaleexpert systems as these are most likely to be of interest tobiologists. The techniques include the use of questionnaires,interview techniques and protocol analysis; particular emphasisis placed on a mod cation to the ‘twenty questions’interview technique which was developed specifically to elicittaxonomic knowledge relating to water mite identification.     

Some approaches to prophylactic measures in a martian expedition

Physiological and methodological principles of the organization of physical training (PT) and its computerization during a space flight to Mars under the conditions of autonomous activity of the crew, including interaction with onboard medical systems, self-maintenance of health, preventive measures, diagnostic examinations, and, if necessary, treatment, are discussed. The conditions of unusually long-term autonomous space flights make the ground-based monitoring of the state of health of crew members substantially more difficult, which calls for computerization of the control over the crew members’ health, including prophylactic measures. The situation is further complicated because it is impossible to receive the necessary information from, and transmit it to, the spacecraft in a real-time mode or to quickly return the crew to Earth in case of an emergency. Under these conditions, physical prevention should be based on an onboard automated expert system ensuring the control over the activities of all crew members aimed at optimizing their psychophysical state. The problems of the control of training, including the use of an onboard automated expert system, are discussed.     

Recent developments and present status of telepathology.

Telepathology which is the diagnostic work of a pathologist at a distance has been developed to routine application within the last ten years. It can be classified in relation to application, technical solutions, or performance conditions. Diagnostic pathology performance distinguishes primary diagnosis (for example, frozen section statement) from secondary diagnosis (for example, expert consultation) and quality assurance (diagnostic accuracy, continuous education and training). Applications comprise (a) frozen section service; (b) expert consultations; (c) remote control measurements; and (d) education and training. The technical solutions distinguish active (remote control, live imaging) systems from passive (conventional microscope handling, static imaging), and the performance systems with interactive (on-line, live imaging) use from those with passive (offline, static imaging) practice. Intra-operative frozen section service is mainly performed with remote control systems; whereas expert consultations and education/training are commonly based upon Internet connections with static imaging in an off-line mode. The image quality, transfer rates, and screen resolution of active and passive telepathology systems are sufficient for an additional or primary judgment of histological slides and cytological smears. From the technical point of view, remote control telepathology requires a fast transfer and at least near on-line judgement of images, i.e., image acquisition, transfer and presentation can be considered one performance function. Thus, image size, line transfer rate and screen resolution define the practicability of the system. In expert consultation, the pixel resolution of images and natural color presentation are the main factors for diagnostic support, whereas the line transfer rate is of minor importance. These conditions define the technical compartments, especially size and resolution of camera and screen. The performance of commercially available systems has reached a high quality standard. Pathologists can be trained in a short time and use the systems in a routine manner. Several telepathology systems have been implemented in large Institutes of Pathology which serve for frozen section diagnosis in small hospitals located in the local area. In contrast, expert consultation is mainly performed with international connections. There is a remarkable increase of expert consultations by telepathology according to the experiences of the Armed Forces Institute of Pathology or the Department of Pathology, Thoraxklinik, Heidelberg. In expansion of these experiences, a "globalization" of telepathology can be expected. Telepathology can be used to shrink the period necessary for final diagnosis by request for diagnostic assistance to colleagues working in appropriate related time zones. Telepathology is, therefore, not a substitute of conventional diagnostic procedures but a real improvement in the world of pathology.     

Artificial neural networks: fundamentals, computing, design, and application

Artificial neural networks (ANNs) are relatively new computational tools that have found extensive utilization in solving many complex real-world problems. The attractiveness of ANNs comes from their remarkable information processing characteristics pertinent mainly to nonlinearity, high parallelism, fault and noise tolerance, and learning and generalization capabilities. This paper aims to familiarize the reader with ANN-based computing (neurocomputing) and to serve as a useful companion practical guide and toolkit for the ANNs modeler along the course of ANN project development. The history of the evolution of neurocomputing and its relation to the field of neurobiology is briefly discussed. ANNs are compared to both expert systems and statistical regression and their advantages and limitations are outlined. A bird's eye review of the various types of ANNs and the related learning rules is presented, with special emphasis on backpropagation (BP) ANNs theory and design. A generalized methodology for developing successful ANNs projects from conceptualization, to design, to implementation, is described. The most common problems that BPANNs developers face during training are summarized in conjunction with possible causes and remedies. Finally, as a practical application, BPANNs were used to model the microbial growth curves of S. flexneri. The developed model was reasonably accurate in simulating both training and test time-dependent growth curves as affected by temperature and pH.     

Quantification of protein-protein interactions using fluorescence polarization.

Quantitative determinations of the dissociation constants of biomolecular interactions, in particular protein-protein interactions, are essential for a detailed understanding of the molecular basis of their specificities. Fluorescence spectroscopy is particularly well suited for such studies. This article highlights the theoretical and practical aspects of fluorescence polarization and its application to the study of protein-protein interactions. Consideration is given to the nature of the different types of fluorescence probes available and the probe characteristics appropriate for the system under investigation. Several examples from the literature are discussed that illustrate different practical aspects of the technique applied to diverse systems.     

Crystalline bodies in parathyroid gland cells ofRana temporaria L.

Summary Cytoplasmic and nuclear crystalline inclusions are described in parathyroid secretory cells of adult frogs (Rana temporaria L.) and their possible significance is discussed.We are indebted to Mr. Raynor L. Jones for his expert technical assistance and to the Science Research Council and the Central Research Fund of London University for awards enabling this work to be performed.     

Fuzzy rule-based Fine–Kinney risk assessment approach for rail transportation systems

Rail transportation is one of the most crucial public transportation types for big and crowded cities. In rail transportation systems, stakeholders face serious issues involved in workshops, stations, lines and their environments, and general office buildings. In order to reach an increased awareness and better occupational health and safety (OHS) management, a new risk assessment approach is proposed in this study. This approach includes a combination of Fine–Kinney method and a fuzzy rule-based expert system. It captures nonlinear causal relationships between Fine–Kinney parameters. Since there is a high level of vagueness involved in the OHS risk assessment data, the rule-based expert system is developed for probability (P), exposure (E), and consequence (C) for evaluating risk score. A case study is carried out in a rail transportation system in Istanbul/Turkey, and a comparison with the classical Fine–Kinney method is discussed. Results of the case study reveal risk clusters and corresponding control measures that should be taken into consideration. The study methodologically contributes to risk assessment in the knowledge, while case study in a real rail transportation system offers an insight into public transport industry in safety improvement.     

基于二叉分类推理的昆虫分类辅助鉴定多媒体专家系统通用平台TaxoKeys的设计与开发

本文详细介绍了基于二叉式分类推理的昆虫分类辅助鉴定多媒体专家系统通用平台TaxoKeys的设计与开发,及其所具备的主要特点。该研究根据昆虫分类学的特点,将昆虫分类的两项式检索表用数据库表示成系统知识库,利用计算机数据结构中二叉树结构的分枝结点搜索技术来实现其推理过程,进行昆虫分类的辅助鉴定,为昆虫分类专家提供一个通用专家系统平台。该系统具有可扩充性好、设计简单、操作方便等特点,同时也适用于一般性生物分类鉴定。另外,本文还就本系统功能的进一步扩展与应用研究等进行了探讨。     

High-cell-density cultivation of microorganisms

High-cell-density cultivation (HCDC) is required to improve microbial biomass and product formation substantially. An overview of HCDC is given for microorganisms including bacteria, archae and eukarya (yeasts). Problems encountered by HCDC and their possible solutions are discussed. Improvements of strains, different types of bioreactors and cultivation strategies for successful HCDC are described. Stirred-tank reactors with and without cell retention, a dialysis-membrane reactor, a gas-lift reactor and a membrane cyclone reactor used for HCDC are outlined. Recently modified traditional feeding strategies and new ones are included, in particular those for unlimited growth to very dense cultures. Emphasis is placed on robust fermentation control because of the growing industrial interest in this field. Therefore, developments in the application of multivariate statistical control, artificial neural networks, fuzzy control and knowledge-based supervision (expert systems) are summarized. Recent advances using Escherichia coli– the pioneer organism for HCDC – are outlined. Received: 20 October 1998 / Received revision: 18 December 1998 / Accepted: 21 December 1998     

Flexible and reconfigurable manufacturing systems paradigms

Reconfigurable Manufacturing System (RMS) is a new manufacturing systems paradigm that aims at achieving cost-effective and rapid system changes, as needed and when needed, by incorporating principles of modularity, integrability, flexibility, scalability, convertibility, and diagnosability. RMS promises customized flexibility on demand in a short time, while Flexible Manufacturing Systems (FMSs) provides generalized flexibility designed for the anticipated variations and built-in a priori. The characteristics of the two paradigms are outlined and compared. The concept of manufacturing system life cycle is presented. The main types of flexibility in manufacturing systems are discussed and contrasted with the various reconfiguration aspects including hard (physical) and soft (logical) reconfiguration. The types of changeability and transformability of manufacturing systems, their components as well as factories, are presented along with their enablers and compared with flexibility and reconfigurability. The importance of having harmonized human-machine manufacturing systems is highlighted and the role of people in the various manufacturing paradigms and how this varies in pursuit of productivity are illustrated. Finally, the industrial and research challenges presented by these manufacturing paradigms are discussed.