This paper, analyzes the defects and its limitations of computer-aided diagnosis system (CADS) in clinical practice in the past, proposes a new pattern CADS of designing method. We used the theory of multidetection, stored the accumulated experience in computer, established the knowledge base, and made the medical diagnosis through maximizing a posteriori (MAP) judgement rule. Statistical data revealed that the CADS had a high accuracy rate. The medical diagnosis can meet the demand for clinical treatments, and realize the clinical diagnostic application of information technology.
Bayes Theorem ; Decision Making, Computer-Assisted ; Diagnosis, Computer-Assisted ; methods ; Humans

In this paper is used the rough set theory to deal with the information contained in electrocardiographic waveforms and to find out the correlation between coronary heart disease (CHD) and the selected indices in electrocardiographic lead I. The principles of attribute reduction are applied, the redundancy of a decision-making table is reduced, and the important characters and diagnostic rules are extracted. The real case analysis shows that clear and concise diagnostic rules can be established by using rough set theory, which can be helpful to the clinical diagnosis of CHD.
Algorithms ; Coronary Disease ; diagnosis ; Decision Making, Computer-Assisted ; Electrocardiography ; methods ; Humans ; Predictive Value of Tests ; Signal Processing, Computer-Assisted

This paper presents a typical Clinical Information System for ICU and its design and implementation. This system is able to capture and archive vital data from the monitor network, providing a whole digital solution in ICU. These vital data can be used in quantitative analysis in the computer-assisted decision support.
Decision Making, Computer-Assisted ; Information Systems ; Intensive Care Units ; Monitoring, Physiologic ; statistics & numerical data ; Software Design

To explore a new method for analyzing biological molecules that have already been sequenced, an experimental study on an auditory method was carried out. The auditory method for analyzing biological molecules includes audible representation of sequence data. Audible representation of sequence data was implemented by using a multimedia computer. Each mononucleotide in a DNA sequence was matched with a corresponding sound, i.e., a DNA sequence was "dubbed" in a sound sequence. When the sound sequence is played, a special cadence can be heard. In the audible representation experiment, special cadences of different exons can be clearly heard. The results show that audible representation of DNA sequence data can be implemented by using a multimedia technique. After a 5-time auditory training, subjects both in internal testing and external testing can obtain 93%-100% of judgment accuracy rate for the difference between two sound sequences of two different exons, thus providing an experimental basis for the practicability of this method. Auditory method for analyzing DNA segments might be beneficial for the research in comparative genomics and functional genomics. This new technology must be robust and be carefully evaluated and improved in a high-throughput environment before its implementation in an application setting.
Computational Biology ; methods ; Decision Making, Computer-Assisted ; Genome ; Humans ; Multimedia ; Sequence Analysis, DNA ; methods ; Sound

BACKGROUNDChinese and contemporary Western medical practices evolved on different cultures and historical contexts and, therefore, their medical knowledge represents this cultural divergence. Computerization of traditional Chinese medicine (TCM) is being used to promote the integrative medicine to manage, process and integrate the knowledge related to TCM anatomy, physiology, semiology, pathophysiology, and therapy.

METHODSWe proposed the development of the SuiteTCM software, a collection of integrated computational models mainly derived from epidemiology and statistical sciences for computerization of Chinese medicine scientific research and clinical practice in all levels of prevention. The software includes components for data management (DataTCM), simulation of cases (SimTCM), analyses and validation of datasets (SciTCM), clinical examination and pattern differentiation (DiagTCM, TongueTCM, and PulseTCM), intervention selection (AcuTCM, HerbsTCM, and DietTCM), management of medical records (ProntTCM), epidemiologic investigation of sampled data (ResearchTCM), and medical education, training, and assessment (StudentTCM).

DISCUSSIONThe SuiteTCM project is expected to contribute to the ongoing development of integrative medicine and the applicability of TCM in worldwide scientific research and health care. The SuiteTCM 1.0 runs on Windows XP or later and is freely available for download as an executable application.

OBJECTIVETo discuss the development module of ontology-based computerized clinical practical guideline, and to supply the technology support for implement of alerm/reminding, data sharing, evidence-based medicine and clinical decision making in the medical information system.

METHODSAnalyse the structure and field ontology of the Guideline Interchange Format (GLIF); expand GLIF based on the Guideline of Cerebrovascular Disease Prevention and Treatment in China and Neurology Disease Ontology.

RESULTSA Chinese computerized guideline of intravenous thrombolytic therapy of acute cerebral infarction is constructed, which included metadata of edition description, list of drug data item, explanation of evidence strength, steps of indications decision, contraindication decision and drug selection.

CONCLUSIONThe computerized clinical practical guideline combined with clinical information system and Electronic Medical Records plays an important role in clinical pathways optimizing and decision making.

Modern medicine generates a great deal of information stored in the medical database. Extracting useful knowledge and providing scientific decision-making for the diagnosis and treatment of disease from the database increasingly becomes necessary. Data mining in medicine can deal with this problem. It can also improve the management level of hospital information and promote the development of telemedicine and community medicine. Because the medical information is characteristic of redundancy, multi-attribution, incompletion and closely related with time, medical data mining differs from other one. In this paper we have discussed the key techniques of medical data mining involving pretreatment of medical data, fusion of different pattern and resource, fast and robust mining algorithms and reliability of mining results. The methods and applications of medical data mining based on computation intelligence such as artificial neural network, fuzzy system, evolutionary algorithms, rough set, and support vector machine have been introduced. The features and problems in data mining are summarized in the last section.
Algorithms ; Automatic Data Processing ; Databases, Factual ; Decision Making, Computer-Assisted ; Decision Trees ; Fuzzy Logic ; Information Storage and Retrieval ; methods ; Neural Networks (Computer)

PURPOSE: This study was designed to develop and evaluate the a web-based simulation program on patient rights education using integrated decision making model into values clarification for nurse students. METHODS: The program was designed based on the Aless & Trollip model and Ford, Trygstad-Durland & Nelms's decision model. Focus groups interviews, surveys on learning needs for patient rights, and specialist interviews were used to develop for simulation scenarios and decision making modules. The simulation program was evaluated between May, 2011 and April, 2012 by 30 student nurses using an application of the web-based program evaluation tools by Chung. RESULTS: Simulation content was composed of two scenarios on patient rights: the rights of patients with HIV and the rights of psychiatric patients. It was composed of two decision making modules which were established for value clarifications, behavioral objective formations, problems identifications, option generations, alternatives analysis, and decision evaluations. The simulation program was composed of screens for teacher and learner. The program was positively evaluated with a mean score of 3.14+/-0.33. CONCLUSION: These study results make an important contribution to the application of educational simulation programs for nurse students' behavior and their decision making ability in protecting the patient rights.
Computer-Assisted Instruction ; Decision Making* ; Education* ; Family Characteristics ; Focus Groups ; HIV ; Human Rights ; Humans ; Learning ; Patient Rights* ; Program Evaluation ; Specialization

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

PURPOSE: To identify the factors affecting the surgical decisions of experienced physicians when treating patients with lower urinary tract symptoms that are suggestive of benign prostatic hyperplasia (LUTS/BPH). METHODS: Patients with LUTS/BPH treated by two physicians between October 2004 and August 2013 were included in this study. The causal Bayesian network (CBN) model was used to analyze factors influencing the surgical decisions of physicians and the actual performance of surgery. The accuracies of the established CBN models were verified using linear regression (LR) analysis. RESULTS: A total of 1,108 patients with LUTS/BPH were analyzed. The mean age and total prostate volume (TPV) were 66.2 (+/-7.3, standard deviation) years and 47.3 (+/-25.4) mL, respectively. Of the total 1,108 patients, 603 (54.4%) were treated by physician A and 505 (45.6%) were treated by physician B. Although surgery was recommended to 699 patients (63.1%), 589 (53.2%) actually underwent surgery. Our CBN model showed that the TPV (R=0.432), treating physician (R=0.370), bladder outlet obstruction (BOO) on urodynamic study (UDS) (R=0.324), and International Prostate Symptom Score (IPSS) question 3 (intermittency; R=0.141) were the factors directly influencing the surgical decision. The transition zone volume (R=0.396), treating physician (R=0.340), and BOO (R=0.300) directly affected the performance of surgery. Compared to the LR model, the area under the receiver operating characteristic curve of the CBN surgical decision model was slightly compromised (0.803 vs. 0.847, P<0.001), whereas that of the actual performance of surgery model was similar (0.801 vs. 0.820, P=0.063) to the LR model. CONCLUSIONS: The TPV, treating physician, BOO on UDS, and the IPSS item of intermittency were factors that directly influenced decision-making in physicians treating patients with LUTS/BPH.
Bayes Theorem ; Decision Making, Computer-Assisted ; Decision Support Techniques ; Humans ; Linear Models ; Lower Urinary Tract Symptoms* ; Prostate ; Prostatic Hyperplasia* ; ROC Curve ; Urinary Bladder Neck Obstruction ; Urodynamics