Aiming at the dilemma of expensive and difficult maintenance, lack of technical data and insufficient maintenance force for modern medical equipment, an intelligent fault diagnosis expert system of multi-parameter monitor based on fault tree was proposed in this study. Firstly, the fault tree of multi-parameter monitor was established and analyzed qualitatively and quantitatively, then based on the analysis results of fault tree, the expert system knowledge base and inference engine were constructed and the overall framework of the system was determined, finally the intelligent fault diagnosis expert system for multi-parameter monitor was developed by using the page hypertext preprocessor (PHP) language, with an accuracy rate of 80% in fault diagnosis. The results showed that technology fusion on the basis of fault tree and expert system can effectively realize intelligent fault diagnosis of multi-parameter monitors and provide troubleshooting suggestions, which can not only provide experience accumulation for fault diagnosis of multi-parameter monitors, but also provide a new idea and technical support for fault diagnosis of medical equipment.
Expert Systems ; Monitoring, Physiologic

This study aims to apply a new expert system to design removable partial denture (RPD) framework. The RPD design is completed in three steps, namely, "selecting missing teeth", "selecting abutment condition", and "selecting personalized clasp". The system can help auxiliary dentists develop personalized treatment plans to reduce their clinical workload. It can also generate a dental preparation guideline for clinical preparation, which can prevent tooth preparation mistakes. By generating the standard electronic drawings of the framework design, the system can reduce the inconvenience caused by manual drawing, thereby facilitating dentist-technician communication and reducing the rate of remade.
Dental Abutments ; Denture Design ; Denture, Partial, Removable ; Expert Systems ; Tooth

New technological advances have paved the way for significant progress in automated urinalysis. Quantitative reading of urinary test strips using reflectometry has become possible, while complementary metal oxide semiconductor (CMOS) technology has enhanced analytical sensitivity and shown promise in microalbuminuria testing. Microscopy-based urine particle analysis has greatly progressed over the past decades, enabling high throughput in clinical laboratories. Urinary flow cytometry is an alternative for automated microscopy, and more thorough analysis of flow cytometric data has enabled rapid differentiation of urinary microorganisms. Integration of dilution parameters (e.g., creatinine, specific gravity, and conductivity) in urine test strip readers and urine particle flow cytometers enables correction for urinary dilution, which improves result interpretation. Automated urinalysis can be used for urinary tract screening and for diagnosing and monitoring a broad variety of nephrological and urological conditions; newer applications show promising results for early detection of urothelial cancer. Concomitantly, the introduction of matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) has enabled fast identification of urinary pathogens. Automation and workflow simplification have led to mechanical integration of test strip readers and particle analysis in urinalysis. As the information obtained by urinalysis is complex, the introduction of expert systems may further reduce analytical errors and improve the quality of sediment and test strip analysis. With the introduction of laboratory-on-a-chip approaches and the use of microfluidics, new affordable applications for quantitative urinalysis and readout on cell phones may become available. In this review, we present the main recent developments in automated urinalysis and future perspectives.
Automation ; Cell Phones ; Creatinine ; Expert Systems ; Flow Cytometry ; Mass Screening ; Mass Spectrometry ; Microfluidics ; Microscopy ; Semiconductors ; Specific Gravity ; Urinalysis* ; Urinary Tract ; Urinary Tract Infections

OBJECTIVES: The usability of clinical information systems (CISs) is known to be an essential consideration in ensuring patient safety as well as integrating clinical flow. This study aimed to determine how usability and safety guidelines of CIS consider clinical workflow through a systematic review in terms of the target systems, methodology, and guideline components of relevant articles. METHODS: A literature search was conducted for articles published from 2000 to 2015 in PubMed, Cochrane, EMBASE, Web of Science, and CINAHL. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement method was employed. Articles containing recommendations, principles, and evaluation items for CIS usability and safety were included. The selected articles were classified according to article type, methodology, and target systems. Taking clinical workflow into consideration, the components of guidelines were extracted and classified. RESULTS: A total of 7,401 articles were identified by keyword search. From the 76 articles remaining after abstract screening, 15 were selected through full-text review. Literature review (n = 7) was the most common methodology, followed by expert opinions (n = 6). Computerized physician order entry (n = 6) was the most frequent system. Four articles considered the entire process of clinical tasks, and two articles considered the principles of the entire process of user interface affecting clinical workflow. Only two articles performed heuristic evaluations of CISs. CONCLUSIONS: The usability and safety guidelines of CISs need improvement in guideline development methodology and with consideration of clinical workflow.
Expert Testimony ; Heuristics ; Hospital Information Systems ; Information Systems* ; Mass Screening ; Medical Order Entry Systems ; Methods ; Patient Safety ; User-Computer Interface

BACKGROUND: Disease diagnosis is complicated since patients may demonstrate similar symptoms but physician may diagnose different diseases. There are a few number of investigations aimed to create a fuzzy expert system, as a computer aided system for disease diagnosis. METHODS: In this research, a cross-sectional descriptive study conducted in a kidney clinic in Tehran, Iran in 2012. Medical diagnosis fuzzy rules applied, and a set of symptoms related to the set of considered diseases defined. The input case to be diagnosed defined by assigning a fuzzy value to each symptom and then three physicians asked about each suspected diseases. Then comments of those three physicians summarized for each disease. The fuzzy inference applied to obtain a decision fuzzy set for each disease, and crisp decision values attained to determine the certainty of existence for each disease. RESULTS: Results indicated that, in the diagnosis of seven cases of kidney disease by examining 21 indicators using fuzzy expert system, kidney stone disease with 63% certainty was the most probable, renal tubular was at the lowest level with 15%, and other kidney diseases were at the other levels. The most remarkable finding of this study was that results of kidney disease diagnosis (e.g., kidney stone) via fuzzy expert system were fully compatible with those of kidney physicians. CONCLUSION: The proposed fuzzy expert system is a valid, reliable, and flexible instrument to diagnose several typical input cases. The developed system decreases the effort of initial physical checking and manual feeding of input symptoms.
Diagnosis ; Expert Systems ; Fuzzy Logic ; Humans ; Iran ; Kidney Calculi ; Kidney Diseases* ; Kidney*

OBJECTIVES: A healthcare decision-making support model and rule management system is proposed based on a personalized rule-based intelligent concept, to effectively manage chronic diseases. METHODS: A Web service was built using a standard message transfer protocol for interoperability of personal health records among healthcare institutions. An intelligent decision service is provided that analyzes data using a service-oriented healthcare rule inference function and machine-learning platform; the rules are extensively compiled by physicians through a developmental user interface that enables knowledge base construction, modification, and integration. Further, screening results are visualized for the self-intuitive understanding of personal health status by patients. RESULTS: A recommendation message is output through the Web service by receiving patient information from the hospital information recording system and object attribute values as input factors. The proposed system can verify patient behavior by acting as an intellectualized backbone of chronic diseases management; further, it supports self-management and scheduling of screening. CONCLUSIONS: Chronic patients can continuously receive active recommendations related to their healthcare through the rule management system, and they can model the system by acting as decision makers in diseases management; secondary diseases can be prevented and health management can be performed by reference to patient-specific lifestyle guidelines.
Chronic Disease* ; Decision Support Systems, Clinical ; Delivery of Health Care* ; Expert Systems ; Health Records, Personal ; Humans ; Knowledge Bases ; Life Style ; Mass Screening ; Self Care

OBJECTIVETo develop an internet-based expert diagnostic system for common respiratory diseases.

METHODSSaaS system was used to build architecture; pattern of forward reasoning was applied for inference engine design; ASP.NET with C# from the tool pack of Microsoft Visual Studio 2005 was used for website-interview medical expert system.The database of the system was constructed with Microsoft SQL Server 2005.

RESULTSThe developed expert system contained large data memory and high efficient function of data interview and data analysis for diagnosis of various diseases.The users were able to perform this system to obtain diagnosis for common respiratory diseases via internet.

CONCLUSIONThe developed expert system may be used for internet-based diagnosis of various respiratory diseases,particularly in telemedicine setting.

OBJECTIVES: Efficient identification of subject experts or expert communities is vital for the growth of any organization. Most of the available expert finding systems are based on self-nomination, which can be biased, and are unable to rank experts. Thus, the objective of this work was to develop a robust and unbiased expert finding system which can quantitatively measure expertise. METHODS: Medical Subject Headings (MeSH) is a controlled vocabulary developed by the National Library of Medicine (NLM) for indexing research publications, articles and books. Using the MeSH terms associated with peer-reviewed articles published from India and indexed in PubMed, we developed a Web-based program which can be used to identify subject experts and subjects associated with an expert. RESULTS: We have extensively tested our system to identify experts from India in various subjects. The system provides a ranked list of experts where known experts rank at the top of the list. The system is general; since it uses information available with the PubMed, it can be implemented for any country. CONCLUSIONS: The expert finding system is able to successfully identify subject experts in India. Our system is unique because it allows the quantification of subject expertise, thus enabling the ranking of experts. Our system is based on peer-reviewed information. Use of MeSH terms as subjects has standardized the subject terminology. The system matches requirements of an ideal expert finding system.
Abstracting and Indexing as Topic ; Bias (Epidemiology) ; Data Mining ; Expert Systems ; India ; Medical Subject Headings* ; National Library of Medicine (U.S.) ; Online Systems ; Professional Competence ; Vocabulary, Controlled

OBJECTIVES: This study demonstrates the feasibility of using expert system shells for rapid clinical decision support module development. METHODS: A readily available expert system shell was used to build a simple rule-based system for the crude diagnosis of vaginal discharge. Pictures and 'canned text explanations' are extensively used throughout the program to enhance its intuitiveness and educational dimension. All the steps involved in developing the system are documented. RESULTS: The system runs under Microsoft Windows and is available as a free download at http://healthcybermap.org/vagdisch.zip (the distribution archive includes both the program's executable and the commented knowledge base source as a text document). The limitations of the demonstration system, such as the lack of provisions for assessing uncertainty or various degrees of severity of a sign or symptom, are discussed in detail. Ways of improving the system, such as porting it to the Web and packaging it as an app for smartphones and tablets, are also presented. CONCLUSIONS: An easy-to-use expert system shell enables clinicians to rapidly become their own 'knowledge engineers' and develop concise evidence-based decision support modules of simple to moderate complexity, targeting clinical practitioners, medical and nursing students, as well as patients, their lay carers and the general public (where appropriate). In the spirit of the social Web, it is hoped that an online repository can be created to peer review, share and re-use knowledge base modules covering various clinical problems and algorithms, as a service to the clinical community.
Archives ; Caregivers ; Decision Making, Computer-Assisted ; Decision Support Systems, Clinical ; Expert Systems ; Humans ; Knowledge Bases ; Peer Review ; Product Packaging ; Software Design ; Students, Nursing ; Tablets ; Uncertainty ; Vaginal Discharge

BACKGROUND: Demands for complicated and long-term administration clinical trials have been increased since investigators actively involved in early stage clinical trials including first-in-human (FIH) trials. Research wards in our clinical trial center were mainly used for phase 1 trials. In order to perform several clinical trials simultaneously during a short period with a minimum number of rooms, beds, and equipment, staffs have to spend a lot of time for efficient operation of limited numbers of facilities. In this study, automated bed-allocation system was developed for efficient scheduling of the research ward based on clinical trial condition and status like experts. METHODS: The system was developed based on clinical trial design, schedule, and the information on research bed and availability stored and updated in database (DB). Automatic assignment system was designed to find an optimal schedule according to the given information using expert rules and algorithms. The optimal solution can be visualized on Gantt chart using C# and Chart FX API. RESULTS: The system was developed to demonstrate the schedule on color chart. It turned out to be well-designed to find an optimal schedule for bed allocation. The system also allows automatic updating of the schedule and information in the DB. CONCLUSION: Automated bed-allocation system developed in this study could save time and improve the efficiency for using space and equipment in clinical trial center. The system can be also applied to similar works or tasks in other fields.
Appointments and Schedules ; Expert Systems ; Humans ; Research Personnel