1.Maxillary sinus floor augmentation: a review of current evidence on anatomical factors and a decision tree.
Mingyue LYU ; Dingyi XU ; Xiaohan ZHANG ; Quan YUAN
International Journal of Oral Science 2023;15(1):41-41
Maxillary sinus floor augmentation using lateral window and crestal technique is considered as predictable methods to increase the residual bone height; however, this surgery is commonly complicated by Schneiderian membrane perforation, which is closely related to anatomical factors. This article aimed to assess anatomical factors on successful augmentation procedures. After review of the current evidence on sinus augmentation techniques, anatomical factors related to the stretching potential of Schneiderian membrane were assessed and a decision tree for the rational choice of surgical approaches was proposed. Schneiderian membrane perforation might occur when local tension exceeds its stretching potential, which is closely related to anatomical variations of the maxillary sinus. Choice of a surgical approach and clinical outcomes are influenced by the stretching potential of Schneiderian membrane. In addition to the residual bone height, clinicians should also consider the stretching potential affected by the membrane health condition, the contours of the maxillary sinus, and the presence of antral septa when evaluating the choice of surgical approaches and clinical outcomes.
Sinus Floor Augmentation
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Decision Trees
2.ECG arrhythmia classification using time frequency distribution techniques.
Safa SULTAN QURRAIE ; Rashid GHORBANI AFKHAMI
Biomedical Engineering Letters 2017;7(4):325-332
In this paper, we focus on classifying cardiac arrhythmias. The MIT-BIH database is used with 14 original classes of labeling which is then mapped into 5 more general classes, using the Association for the Advancement of Medical Instrumentation standard. Three types of features were selected with a focus on the time-frequency aspects of ECG signal. After using the Wigner-Ville distribution the time-frequency plane is split into 9 windows considering the frequency bandwidth and time duration of ECG segments and peaks. The summation over these windows are employed as pseudo-energy features in classification. The “subject-oriented” scheme is used in classification, meaning the train and test sets include samples from different subjects. The subject-oriented method avoids the possible overfitting issues and guaranties the authenticity of the classification. The overall sensitivity and positive predictivity of classification is 99.67 and 98.92%, respectively, which shows a significant improvement over previous studies.
Arrhythmias, Cardiac*
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Classification*
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Decision Trees
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Electrocardiography*
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Methods
3.The clinical decision analysis using decision tree.
Epidemiology and Health 2014;36(1):e2014025-
The clinical decision analysis (CDA) has used to overcome complexity and uncertainty in medical problems. The CDA is a tool allowing decision-makers to apply evidence-based medicine to make objective clinical decisions when faced with complex situations. The usefulness and limitation including six steps in conducting CDA were reviewed. The application of CDA results should be done under shared decision with patients' value.
Decision Support Techniques*
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Decision Trees*
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Evidence-Based Medicine
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Uncertainty
4.Development of Customer Relationship Management System in the Healthcare Domain Using Data Mining.
Journal of Korean Society of Medical Informatics 2004;10(3):303-310
OBJECTIVE: To provide medicare services for patients demands satisfyingly, immediate introduction of the Customer Relationship Management(CRM) is raised inevitable. In this paper we proposed that the minimizing the hospital losses by cut down the rate of cancelation of the hospital reservation, to secure patients as clients. METHODS: And to implement the data mining-based healthcare customer relationship management system applied from the back propagation algorithm of the artificial neural networks technique and the Feature GENeration(FGEN) algorithm of the decision tree technique. RESULTS: In this paper we divided a patient to an appropriate group through a data mining process and classified more correct customer through a campaign process. CONCLUSION: These results would be essential for new patients to enhance hospital reliability, for hospital to select profitable patients with high loyalty and to manage patients efficiently.
Data Mining*
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Decision Trees
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Delivery of Health Care*
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Humans
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Medicare
5.Application of Decision Tree for the Classification of Antimicrobial Peptide.
Su Yeon LEE ; Sunkyu KIM ; Sukwon S KIM ; Seon Jeong CHA ; Young Keun KWON ; Byung Ro MOON ; Byeong Jae LEE
Genomics & Informatics 2004;2(3):121-125
The purpose of this study was to investigate the use of decision tree for the classification of antimicrobial peptides. The classification was based on the activities of known antimicrobial peptides against common microbes including Escherichia coli and Staphylococcus aureus. A feature selection was employed to select an effective subset of features from available attribute sets.Sequential applications of decision tree with 17 nodes with 9 leaves and 13 nodes with 7 leaves provided the classification rates of 76.74% and 74.66% against E. coli and S. aureus, respectively. Angle subtended by positively charged face and the positive charge commonly gave higher accuracies in both E. coli and S. aureus datasets. In this study, we describe a successful application of decision tree that provides the understanding of the effects of physicochemical characteristics of peptides on bacterial membrane.
Classification*
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Dataset
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Decision Trees*
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Escherichia coli
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Membranes
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Peptides
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Staphylococcus aureus
6.Research on medical data mining and its applications.
Journal of Biomedical Engineering 2014;31(5):1182-1186
With the development of computer technology, medical data has developed from traditional paper pattern into electronic mode, which could effectively promote the medical development. This paper at first presents the status and characteristics of medical data mining. Then, it discusses the critical method of medical data mining in classification, clustering and prediction, respectively. The paper focuses on the application and assessment of five algorithms which are designed for medical data mining, including decision tree, cluster analysis, association rule, intelligent algorithm and the mix algorithm. Finally, this paper outlooks the data mining application in medical domain.
Algorithms
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Cluster Analysis
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Data Mining
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Decision Trees
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Medical Informatics
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Software
7.Which Bisphosphonate? It's the Compliance!: Decision Analysis.
You Jin LEE ; Chan Ho PARK ; Young Kyun LEE ; Yong Chan HA ; Kyung Hoi KOO
Journal of Bone Metabolism 2016;23(2):79-83
BACKGROUND: The best options of several bisphosphonates for prevention of osteoporotic fractures in postmenopausal women remain controversial. We determined which bisphosphonate provides better efficacy in prevention of osteoporotic fractures using a decision analysis tool, in terms of quality of life. METHODS: A decision analysis model was constructed containing final outcome score and the probability of vertebral and hip fracture within 1 year. Final outcome was defined as health-related quality of life, and was used as an utility in the decision tree. Probabilities were obtained by literature review, and health-related quality of life was evaluated by consensus committee. A roll back tool was used to determine the best bisphosphonate, and sensitivity analysis was performed to compensate for decision model uncertainty. RESULTS: The decision model favored bisphosphonate with higher compliance in terms of quality of life. In one-way sensitivity analysis, ibandronate was more beneficial than the others, when probability of compliance on ibandronate was above 0.589. CONCLUSIONS: In terms of quality of life, the decision analysis model showed that compliance was most important for patients in real world, regardless of type of bisphosphonate.
Compliance*
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Consensus
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Decision Support Techniques*
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Decision Trees
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Diphosphonates
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Female
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Hip
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Humans
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Osteoporotic Fractures
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Patient Compliance
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Quality of Life
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Uncertainty
8.Self-efficacy and Compliance in Patients with Chronic Heart Failure: The Effect of a Self-management Program using Decision Tree.
Cho Ja KIM ; Gi Yon KIM ; Yeon Soo JANG
Journal of Korean Academy of Adult Nursing 2004;16(2):316-326
PURPOSE: The purpose of this study was to identify effects of a self-management program on self-efficacy and compliance in patients with CHF. Hypothesis: 1) Patients with CHF who are provided with a self-management program will show higher self-efficacy scores than a control group. 2) Patients who are provided with a self-management program will show higher compliance scores than a control group. METHOD: This study was designed as a nonequivalent non-synchronized pre-posttest control group. There were eight patients in the experimental group, and twelve in the control group. According to NYHA classification, all patients belonged under the classesl to lV. Data were collected using the instruments developed by the researchers. Data were analyzed using descriptive statistics and Mann Whitney U test. RESULT: There were significant differences in self-efficacy scores and compliance scores between the experimental and control group. CONCLUSION: By utilizing the program, patients were able to monitor their symptoms routinely, comply with therapeutic regimen, and feel better able to positively influence their disease. Therefore, better compliance means fewer readmissions of patients with CHF.
Classification
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Compliance*
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Decision Trees*
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Heart Failure*
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Heart*
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Humans
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Self Care*
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Statistics, Nonparametric
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Surveys and Questionnaires
9.Development of the Computer-Assisted HACCP System Program and Developing HACCP-Based Evaluation Tools of Sanitation for Institutional Foodservice Operations.
Jaung Sook LEE ; Hee Jung HONG ; Tong Kyung KWAK
Korean Journal of Community Nutrition 1998;3(4):655-667
The Computer-assisted Hazard Analysis and Critical Control Point(HACCP) program has been developed for a systematic implementation of HACCP principles in identifying, assessing and controlling hazards in institutional foodservics operations. The HACCP-based sanitation evaluation tool has been developed, based on the results of the computerized assisted HACCP program in 4 service sites of C contracted foodservice company, including 2 general hospitals with 650-beds, one office operation of 400 meals per day, and one factory foodservice of 1,000 meals per day. All database files and processing programs were created by using Unify Vision tool with Windows 95 of user environments. The results of this study can be summarized as follows : 1. This program consists of the pre-stage for HACCP study and the implementation stage of the HACCP system. 1) The pre-stage for HACCP study includes the selection of menu items, the development of the HACCP recipe, the construction of product flow diagrams, and printing the HACCP recipes and product flow diagrams. 2) The implementation of the HACCP system includes the identification of microbiological hazards, the determination of critical control points based on the decision tree base files. 3) The HACCP-based sanitation evaluation tool consisted of 3 dimensions of time-temperature relationship, personal hygiene, and equipment-facility sanitation. The Cronbach's alphas calculation indicated that the tool was reliable. The results showed that the focus groups rated the mean of importance in time-temperature relationship, personal hygiene, and equipment-facility sanitation as 4.57, 4.59 and 4.55 respectively. Based on the results, this HACCP-based sanitation evaluation tool was considered as an effective tool for assuring product quality. This program will assist foodservice managers to encourage a standardized approach in the HACCP study and to maintain a systematic approach for ensuring that the HACCP principles are applied correctly.
Decision Trees
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Focus Groups
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Hazard Analysis and Critical Control Points*
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Hospitals, General
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Humans
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Hygiene
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Meals
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Sanitation*
10.An Application of Data Mining Approach to CQI Using the Discharge Summary.
Mi Ohk SUHN ; Young Moon CHAE ; Hae Jong LEE ; Sun Hee LEE ; Sung Hong KANG ; Seung Hee HO
Journal of Korean Society of Medical Informatics 2000;6(4):1-13
This study provides an application of datamining approach to CQJ using the discharge summary. First, we found a process variation in hospital infection rate by SPC (Statistical Process Control) technique. Second, importance of factors influencing hospital infection was inferred through the decision tree analysis which is a classification method in data -mining approach. The most important factor was surgery followed by comorbidity and length of operation. Comorbidity was further divided into age and principal diagnosis and the length of operation was further divided into age and chief complaint. 24 rules of hospital infection were generated by the decision tree analysis. Of these, 9 rules with predictive prover greater than 50% were suggested as guidelines for hospital infection control. The optimum range of target group in hospital infection control were identified through the information gain summary.Association rule, which is another kind of datamining method, was performed to analyze the relationship between principal diagnosis and comorbidity. The confidence score, which measures the degree of association, between urinary tract infection and causal bacillus was the highest, followed by the score between postoperative wound disruption and postoperative wound infection.This study demonstrated how datamining approach could be used to provide information to support prospective surveillance of hospital infection. The datamining technique can also be applied to various areas for CQI using other hospital databases.
Bacillus
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Classification
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Comorbidity
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Cross Infection
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Data Mining*
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Decision Trees
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Diagnosis
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Urinary Tract Infections
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Wounds and Injuries