Proper Features Extraction from the Multiple Sclerosis Disease Postural Disorders for Decision Support System Definition

2014 ◽  
Vol 666 ◽  
pp. 230-234 ◽  
Author(s):  
Hakimeh Pourakbari ◽  
Yashar Sarbaz ◽  
Jalal Parvin ◽  
Mohammad Hossein Vojudi
Keyword(s):  
Multiple Sclerosis ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Neurological Diseases ◽  
Statistical Tests ◽  
Multiple Sclerosis Disease ◽  
Advanced Stages ◽  
Firm Basis ◽  
Postural Disorders

Multiple Sclerosis (MS) is one of the most common neurological diseases that it is often progressive and disabling. Its main cause is destruction of myelin sheaths by the immune system. Myelin damage seriously affects people’s physical activities, such as postural impairments. Early detection of the disease is very important in disease management. Unfortunately, currently there is no definite test for MS diagnosis. Of course, there are some tests that help to confirm the diagnosis in advanced stages of the disease butnone of them can independently confirm the disease and have some restrictions and errors. It seems that quantitative analysis of movement disorders especially postural disorders can be helpful in diagnosis of MS even in its early stages. In this study, posturalimpairment was studied. First postural disorders were extracted, then obtained signals were processed quantitatively sovariance and proper frequency features were extracted. At the end, using statistical tests it was shown that these features were significantly different. Therefore based on the results it is possible to design a classifier that can be a firm basis for presenting Decision Support System (DSS) for multiple sclerosis diagnosis.

scholarly journals Advanced Managerial Accounting Techniques and Decision Support System: An Empirical Analysis of Small And Medium Enterprises in Jordan

2018 ◽  
Vol 14 (22) ◽  
pp. 233
Author(s):  
Wesam Abu Mater ◽  
H. Kanasro
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Empirical Analysis ◽  
Support System ◽  
Small And Medium Enterprises ◽  
Statistical Tests ◽  
Social Variables ◽  
Managerial Accounting ◽  
Use Of Technology ◽  
Medium Enterprises

This study investigates the empirical analysis of advanced managerial accounting techniques on decision support system in small and medium enterprises in Jordan. The crucial role played by small and medium-sized companies have a major impact on the economies of countries. Therefore, working at maximum cost-effectiveness is vital to both survival and competitiveness because most SMEs in developing countries operate in crowded and competitive markets. To obtain the objectives of the study, the researcher conducted a questionnaire survey, a sample was of 100 managers and 200 employees’ respondents was purposefully sampled, in SMEs in Amman capital city of Jordan. The purpose of the sample is to see the effect of accounting management techniques and decision support system in small and medium enterprises and the researcher take the demographic variables; gender, management level, age, education, and use of technology and financial controlling systemare taken as moderating variables. The statistical tests were applied to analyze the data. The results of the study showed the significant impact of advanced managerial accounting techniques and decision support on SMEs. The study also found that financial controlling system and the use of technology has a positive impact on performance. In light of the results the researcher has made a number of recommendations that will help the Jordanian enterprises, in order to be able to interact and respond to economic, environmental and social variables and respond to economic, environmental and social variables.

ANALISIS RAGAM DIALOG DIAGNOSIS PENYAKIT BERBASIS SPK MODEL TAM DENGAN SEMPLS

Jurnal Varian ◽  
2018 ◽  
Vol 1 (2) ◽  
pp. 50-58
Author(s):  
Sandi Justitia Putra ◽  
Jian Budiarto ◽  
Jihadil Qudsi
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Natural Language ◽  
Physical Examination ◽  
Technology Acceptance ◽  
Support System ◽  
Interface Design ◽  
Statistical Tests ◽  
Menu System ◽  
Natural Language Process

Decision Support System provides problem solving with semi structured and unstructured conditions. Decision Support System also has a role in the medical world, used in diagnosing diseases based on examination of patients. But often occurs less implementation due to the system interface interface that is not in accordance with the wishes of users. System interface interface tested there are 3 stages, namely anamnesis stage, physical examination stage, and examination. The choices given to the respondents are 3 interface design with various dialogue techniques for the anamnesis and physical examination phase ie Natural Language Process, Menu System and Filling Form and 2 interface design for supporting investigation ie Windowing System and Graphic Interaction. After the respondents made a choice on the questionnaire sheet, statistical tests were performed based on the Technology Acceptance Model. The result of the analysis shows the design according to the respondent's wishes on the decision support system to diagnose the disease at the anamnesis stage and physical examination stage is the design of the interface system with the filling form because of the larger R square model value at each stage of the interface design Natural Language Process and Menu System , while the supporting stage is the graphical interface interaction design on the graphical display, because of the larger R square model values ​​at each stage of the windowing system interface design.

scholarly journals Determination of Minimum Data Set for Designing a Diagnosis Decision Support System and Medication Follow-Up for Multiple Sclerosis

2020 ◽  
Author(s):  
Sahar Khenarinezhad ◽  
Niloofar Mohammadzadeh ◽  
Marjan GhaziSaeedi ◽  
Abdorreza NaserMoghadasi
Keyword(s):  
Multiple Sclerosis ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Medical Training ◽  
Cross Sectional ◽  
Data Set ◽  
History Of ◽  
Minimum Dataset

Background and Purpose: Diagnosis of multiple sclerosis (MS) is complicated because of the lack of definite factor. Decision support systems are expert systems which help physicians in decision-making process. First step in designing the system is identification of a minimum dataset (MDS). This study aimed to determine minimum dataset required to design diagnosis decision support system.Materials and Methods: This research was a descriptive cross-sectional study. Data were gathered from medical guideline approved by Ministry of Health, Treatment and Medical Training, Multiple Sclerosis diagnosis, international guideline of Royal college of England, and McDonald Diagnostic criteria. Data collection tool was a designed checklist consisting of 100 items provided to 25 neurologists and MS fellowships of medical universities and private clinics in Iran.Results: Out of 100 designed information’s items, 10 items were omitted due to CVR less than 0.49. Employment status items, history of MS in 3rd grade relatives, history of viral diseases, orbital MRI, optical coherence tomography, brain CT-scan, ESR, CRP, visually evoked potentials, delay duration of P100 for each eyes are all examples of information elements that have been omitted.Conclusion: Determining the minimum dataset related to MS is an important step in designing diagnosis decision support system and medication follow-up. Therefore, MDSs can help those responsible for gathering standard information of patients with Multiple Sclerosis (MS), and causes improvement in management of information for this disease.

INTRODUCING A DECISION SUPPORT SYSTEM FOR MULTIPLE SCLEROSIS BASED ON POSTURAL TREMOR: A HOPE FOR SEPARATION OF PEOPLE WHO MIGHT BE AFFECTED BY MULTIPLE SCLEROSIS IN THE FUTURE

2017 ◽  
Vol 29 (06) ◽  
pp. 1750046
Author(s):  
Yashar Sarbaz ◽  
Hakimeh Pourakbari ◽  
Mohammad Hossein Vojudi ◽  
Ahmad Ghanbari
Keyword(s):  
Multiple Sclerosis ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Healthy Subjects ◽  
High Accuracy ◽  
Test Method ◽  
Artificial Neural Network Classifier ◽  
The Future ◽  
Balance Disorder

Multiple Sclerosis (MS) is a progressive and disabling autoimmune disease of the Central Nervous System (CNS). Regretfully, no reliable MS diagnostic test has been proposed so far. Early diagnosis of the disease has significant benefits. Based on studies, it seems that the movement disorders have a good potential to help the researchers diagnose MS in its early stages. The main objective of this study was to propose a decision support system (DSS) for MS based on balance disorder. To this end, 14 MS patients and 20 healthy subjects were recruited in this study. An infrared marker was set on the participants’ forehead and in between eyebrows. They were asked to stand silently in front of a black background for 3[Formula: see text]min with their feet shoulder-width apart. Their balance disorder was recorded with a camcorder. Then, the video images were analyzed using MATLAB software and an image processing algorithm was used to get the marker position on images. In the next step, appropriate features that had the ability to separate healthy subjects from patients were extracted. Finally, an artificial neural network classifier was designed that could separate the patients from healthy subjects with high accuracy (92.35%). Due to the high accuracy of the classifier, it can be used as a system in order to introduce a DSS for the diagnosis of MS. Besides, an intermediate state between healthy and diseased states was imagined and people belonging to this state were simulated based on their features behaviors. Hence, another classifier was designed with accuracy of 84.8%. It seems that the second classifier is capable of separating people suspected of having MS in the future. The main contribution of this study is the classification of suspected cases of having MS in the future. Moreover, the presented DSS is simple, easy to use and has high accuracy. As the presented test method is simple and the duration of imaging time is only 3[Formula: see text]min, it can be performed annually as a routine checkup and immediately after the observation of the slightest disturbances in the postural behavior the person can be asked to visit a specialist for a more detailed examination.

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