scholarly journals ПРОГНОЗУВАННЯ ТА ПРИЙНЯТТЯ РІШЕНЬ В УМОВАХ НЕВИЗНАЧЕНОСТІ В ПРОБЛЕМАХ СИСТЕМНИХ МЕДИЧНИХ ДОСЛІДЖЕНЬ

2017 ◽  
Author(s):  
V. P. Martsenyuk ◽  
I Ye. Andrushchak
Keyword(s):  
Data Mining ◽  
Support System ◽  
System Analysis ◽  
Medical System ◽  
Information Support ◽  
System Research ◽  
Data Mining Algorithms ◽  
Analysis Methods ◽  
Mining Algorithms ◽  
Information Support System

The work presents our results in field of application of system analysis methods to problem of medical research. We emphasize effects of uncertainty that should be taken into account in such complex processes. Medical system research requires information support system implementing data mining algorithms resulting in decision trees or IF-THEN rules. Besides that such system should be object-oriented and web-integrated.The aim of this study was to develop information support system based on data mining algorithms applied to system analysis method for medical system research. System analysis methods were used for qualitative analysis of diseases mathematical models. Algorithms such as decision tree induction and sequential covering algorithm were applied for data mining from learning data set.We observed the complex qualitative behavior of population and diseases models depending on parameters and controllers even without considering probabilistic nature of the most of quantities and parameters of information models.

scholarly journals INFORMATION SUPPORT SYSTEM OF MEDICAL SYSTEM RESEARCH

2014 ◽  
Vol 1 (1) ◽  
Author(s):  
V. P. Martsenyuk ◽  
I. Ye. Andrushchak
Keyword(s):  
Data Mining ◽  
Qualitative Analysis ◽  
Support System ◽  
System Analysis ◽  
Medical System ◽  
Information Support ◽  
System Research ◽  
Data Mining Algorithms ◽  
Mining Algorithms ◽  
Information Support System

Background. Medical system research requires information support system of implementing data mining algorithms resulting in decision trees or IF-THEN rules. Besides that, this system should be object-oriented and web-integrated.Objective. The aim of this study was to develop information support system based on data mining algorithms applied to system analysis method for medical system research.Methods. System analysis methods are used for qualitative analysis of mathematical models diseases. Algorithms such as decision tree induction and sequential covering algorithm are applied for data mining from learning data set.Results. Taking into consideration the complexity of mathematical equations (nonlinear systems with delays), scientific community requires the appearance of new powerfull methods of exact parameter identification and qualitative analysis. From the point of view of theoretical medicine, uncertainties arising in models of diseases require to develop treatment schemes that are effective, take into account toxicity constraints, enable better life quality, have cost benefit. Multivariate method of qualitative analysis of mathematical models can be used for pathologic process forms of classification.Conclusions. The complex qualitative behavior of diseases models depending on parameters and controllers was observed in our investigation even without considering probabilistic nature of the majority of quantities and parameters of information models.KEY WORDS: data mining, system analysis, medical research, decision making

scholarly journals Information support system for Alzheimer’s disease patients’ caregivers in Croatia: a phenomenological approach

2020 ◽  
Author(s):  
Kornelija Petr Balog ◽  
◽  
Sanjica Faletar Tanackovic ◽  
Sanda Erdelez ◽  
◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Support System ◽  
Interpretative Phenomenological Analysis ◽  
Information Needs ◽  
System Analysis ◽  
Information Support ◽  
Family Doctors ◽  
Health And Social Care ◽  
Information Support System

Introduction. The paper presents findings from a study that investigated information needs of caregivers of Alzheimer’s disease patients’ in Croatia, a country in which health and social care systems for such persons are insufficiently developed. Special emphasis is put on the barriers caregivers face in obtaining required information or services. Methods. Interviews with 11 Alzheimer’s disease patients’ caregivers from the area of Eastern Croatia were conducted. Interpretative phenomenological analysis was chosen as the best method to interpret the caregivers’ experience of information support received from the Croatian system. Analysis. Topics were defined for each interview and then superordinate topics were defined for the whole sample. Results. Results show that Alzheimer’s disease patients’ caregivers in Croatia are faced with numerous obstacles. No organised information support system was detected. Conclusions. A more holistic approach to information support is needed. Authors suggest an Alzheimer’s disease information package to be distributed through the family doctors’ practices.

scholarly journals Data Mining Algorithms for Pharmacovigilance

2019 ◽  
Vol 9 (1S) ◽  
pp. 81-85
Keyword(s):  
Data Mining ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Classification Accuracy ◽  
Specific Drug ◽  
Data Mining Algorithms ◽  
Good Classification ◽  
Mining Algorithms ◽  
Aided Diagnosis

In this paper, various data mining algorithms for pharmacovigilance is analyzed and a decision support system for hospital is proposed.. Overall analysis of adverse events of a specific drug helps in finding the potential danger of using the specific drug. Decision support system with good classification accuracy to improve its use in hospital for computer aided diagnosis by doctors is also analyzed,

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