scholarly journals Data Analysis and Data Mining: Current Issues in Biomedical Informatics

2011 ◽  
Vol 50 (06) ◽  
pp. 536-544 ◽  
Author(s):  
M. Diomidous ◽  
I. N. Sarkar ◽  
K. Takabayashi ◽  
A. Ziegler ◽  
A. T. McCray ◽  
...  
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Data Analysis ◽  
Knowledge Integration ◽  
Biomedical Informatics ◽  
Data Driven ◽  
Biomedical Data ◽  
Translational Bioinformatics ◽  
Biomedical Sciences ◽  
Mining Methods

SummaryBackground: Medicine and biomedical sciences have become data-intensive fields, which, at the same time, enable the application of data-driven approaches and require sophisticated data analysis and data mining methods. Biomedical informatics provides a proper interdisciplinary context to integrate data and knowledge when processing available information, with the aim of giving effective decision-making support in clinics and translational research.Objectives: To reflect on different perspectives related to the role of data analysis and data mining in biomedical informatics. Methods: On the occasion of the 50th year of Methods of Information in Medicine a symposium was organized, which reflected on opportunities, challenges and priorities of organizing, representing and analysing data, information and knowledge in biomedicine and health care. The contributions of experts with a variety of backgrounds in the area of biomedical data analysis have been collected as one outcome of this symposium, in order to provide a broad, though coherent, overview of some of the most interesting aspects of the field.Results: The paper presents sections on data accumulation and data-driven approaches in medical informatics, data and knowledge integration, statistical issues for the evaluation of data mining models, translational bioinformatics and bioinformatics aspects of genetic epidemiology.Conclusions: Biomedical informatics represents a natural framework to properly and effectively apply data analysis and data mining methods in a decision-making context. In the future, it will be necessary to preserve the inclusive nature of the field and to foster an increasing sharing of data and methods between researchers.

scholarly journals Application of Intellectual Methods of Data Analysis to Improve the Quality of Decision Making in Management of Resources for the Information Media System

2021 ◽  
Vol 27 (1) ◽  
pp. 014-019
Author(s):  
K. B. Shabanov ◽  
◽  
V. V. Alekseev ◽  
Keyword(s):  
Data Mining ◽  
Neural Networks ◽  
Decision Making ◽  
Fuzzy Logic ◽  
Data Analysis ◽  
Media System ◽  
Management Of Resources ◽  
Mining Methods ◽  
Information Media

In connection with the relevance of data analysis automation, basic data mining methods are considered, such as neural networks, genetic algorithms, and fuzzy logic methods. The essence of these methods and their practical applicability are shown, in particular, methods of fuzzy logic for the problem of improving the quality of decision-making when managing the resources of the information media system.

Stamping Plant 4.0 – Basics for the Application of Data Mining Methods in Manufacturing Car Body Parts

2015 ◽  
Vol 639 ◽  
pp. 21-30 ◽  
Author(s):  
Stephan Purr ◽  
Josef Meinhardt ◽  
Arnulf Lipp ◽  
Axel Werner ◽  
Martin Ostermair ◽  
...  
Keyword(s):  
Data Mining ◽  
Data Acquisition ◽  
Data Driven ◽  
Quality Analysis ◽  
Process Conditions ◽  
Data Sets ◽  
Body Parts ◽  
Car Body ◽  
Sample Data ◽  
Mining Methods

Data-driven quality evaluation in the stamping process of car body parts is quite promising because dependencies in the process have not yet been sufficiently researched. However, the application of data mining methods for the process in stamping plants would require a large number of sample data sets. Today, acquiring these data represents a major challenge, because the necessary data are inadequately measured, recorded or stored. Thus, the preconditions for the sample data acquisition must first be created before being able to investigate any correlations. In addition, the process conditions change over time due to wear mechanisms. Therefore, the results do not remain valid and a constant data acquisition is required. In this publication, the current situation in stamping plants regarding the process robustness will be first discussed and the need for data-driven methods will be shown. Subsequently, the state of technology regarding the possibility of collecting the sample data sets for quality analysis in producing car body parts will be researched. At the end of this work, an overview will be provided concerning how this data collection was implemented at BMW as well as what kind of potential can be expected.

Integrating OLAP/SOLAP in E-Business Domains

2011 ◽  
Vol 24 (3) ◽  
pp. 45-60
Author(s):  
Ben Ali ◽  
Samar Mouakket
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Data Analysis ◽  
United Arab Emirates ◽  
Decision Makers ◽  
Job Seekers ◽  
Job Market ◽  
Analysis Techniques ◽  
Analytical Processing ◽  
User Friendly

E-business domains have been considered killer domains for different data analysis techniques. Most researchers have examined data mining (DM) techniques to analyze the databases behind E-business websites. DM has shown interesting results, but this technique presents some restrictions concerning the content of the database and the level of expertise of the users interpreting the results. In this paper, the authors show that successful and more sophisticated results can be obtained using other analysis techniques, such as Online Analytical Processing (OLAP) and Spatial OLAP (SOLAP). Thus, the authors propose a framework that fuses or integrates OLAP with SOLAP techniques in an E-business domain to perform easier and more user-friendly data analysis (non-spatial and spatial) and improve decision making. In addition, the authors apply the framework to an E-business website related to online job seekers in the United Arab Emirates (UAE). The results can be used effectively by decision makers to make crucial decisions in the job market of the UAE.

CURRENT RESEARCH TREND: INFORMATION TECHNOLOGY AND DECISION MAKING IN 2008

2009 ◽  
Vol 08 (01) ◽  
pp. 1-5 ◽  
Author(s):  
YONG SHI
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Information Technology ◽  
Decision Analysis ◽  
Credit Scoring ◽  
Advisory Board ◽  
Research Trend ◽  
Web Based ◽  
Mining Methods ◽  
New Research

On behalf of the editorial advisory board of the International Journal of Information Technology and Decision Making (IT&DM), the Editor-in-Chief reviews the current research trend of this journal based on all the papers published in 2008. They are web-based decision analysis, credit scoring techniques and new data mining methods which combine both decision-making techniques and information technology tools. In addition, the Editor-in-Chief summarizes the key ideas of contributions in this new issue that may contain new research trend of IT&DM in 2009.

Data analysis of information system TURAWA in the aspect of data mining methods

2018 ◽  
Vol 0 (7/2018) ◽  
pp. 45-52
Author(s):  
Bolesław Szafrański ◽  
Mirosław Zieja ◽  
Jarosław Wójcik ◽  
Krzysztof Murawski
Keyword(s):  
Data Mining ◽  
Information System ◽  
Data Analysis ◽  
Computer System ◽  
Air Force ◽  
Armed Forces ◽  
Flight Safety ◽  
Operation Process ◽  
Mining Methods ◽  
Extract Information

The article is devoted to the analysis of data coming from the operation process and collected in computer system TURAWA, which focuses on supporting the management of flight safety in the Polish Air Force. The Armed Forces are equipped with a system, which collects and processes data concerning the whole air crew, all performed flights and all aircraft. The increasing opportunities in obtaining data and the continuous development of data mining methods allow to extract information never been known before, which, together with conclusions obtained from the data analysis, will help to improve the level of flight safety.

scholarly journals Automated Decision-Making and Environmental Impact Assessments: Decisions, Data Analysis and Predictions

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Zoe Nay ◽  
Anna Huggins ◽  
Felicity Deane
Keyword(s):  
Decision Making ◽  
Data Analysis ◽  
Environmental Impact ◽  
Environmental Law ◽  
Critical Role ◽  
Data Driven ◽  
Data Driven Decision Making ◽  
Environmental Impact Assessments ◽  
Decision Making Processes ◽  
Automated Decision Making

This article critically examines the opportunities and challenges that automated decision-making (ADM) poses for environmental impact assessments (EIAs) as a crucial aspect of environmental law. It argues that while fully or partially automating discretionary EIA decisions is legally and technically problematic, there is significant potential for data-driven decision-making tools to provide superior analysis and predictions to better inform EIA processes. Discretionary decision-making is desirable for EIA decisions given the inherent complexity associated with environmental regulation and the prediction of future impacts. This article demonstrates that current ADM tools cannot adequately replicate human discretionary processes for EIAs—even if there is human oversight and review of automated outputs. Instead of fully or partially automating EIA decisions, data-driven decision-making can be more appropriately deployed to enhance data analysis and predictions to optimise EIA decision-making processes. This latter type of ADM can augment decision-making processes without displacing the critical role of human discretion in weighing the complex environmental, social and economic considerations inherent in EIA determinations.

scholarly journals Analisis Pola Pembelian Obat di Apotek Sekar Adi Menggunakan Metode Algoritma Apriori Depok

2020 ◽  
Vol 4 (1) ◽  
pp. 112
Author(s):  
Siti Awaliyah Rachmah Sutomo ◽  
Frisma Handayanna
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Association Rules ◽  
High Frequency ◽  
Apriori Algorithm ◽  
Transaction Data ◽  
Mining Methods ◽  
Using Data ◽  
Purchase Patterns

By using data mining methods can be processed to obtain information and assist in decision making, the amount of data on sales transactions in each drug purchase can cause a data accumulation and various problems, such as drug stock inventory, and sales transaction data, with Data mining techniques, the behavior of consumers in making transactions of drug purchase patterns can be analyzed, It can be known what drugs are commonly purchased by mostly people, the application of Apriori Algorithm is expected to help in forming a combination of itemset. The process of determining drug purchase patterns can be carried out by applying the Appriori algorithm method, determination of drug purchase patterns can be done by looking at the results of the consumer's tendency to buy drugs based on a combination of 3 itemset. By calculating the Analysis of High Frequency Patterns and the Formation of Association Rules, with a minimum of 30% support, there is a combination of 3 itemsset namely MOLAGIT PER TAB (M1), VIT C TABLET (V2), and PARACETAMOL 500 MG TABLET (P2) with 33.33 % support results obtained, and with minimum confidence of 65% there are 6 final association rules.

scholarly journals A Literature Survey on Data Mining Approach to Effectively Handle Cancer Treatment

2018 ◽  
Vol 7 (2.7) ◽  
pp. 729 ◽  
Author(s):  
Sri Hari Nallamala ◽  
Siva Kumar Pathuri ◽  
Dr Suvarna Vani Koneru
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Data Analysis ◽  
Cancer Treatment ◽  
User Interaction ◽  
Medical Practitioner ◽  
Vital Role ◽  
Healthcare Management ◽  
Clinical Approach ◽  
Internet Resource

The effective treatment of cancer is not very easy since diagnosis of cancer involves many stages of treatment with gradually changing lifestyles. Physicians play vital role in identifying the correct cause and feel ambiguity for making perfect decisions about hundreds of data available from the internet resource. IDA (Intelligent Data Analysis) which is a part from Data Mining techniques is quiet useful to most of the physicians for decision making about types of cancers. IDA facilitates physicians to classify, detect and analyze the cancer outcome to patients. Healthcare Management System also aids the practitioners to practically search, analyze and compare the result analysis of the patient with existing data in the HMS and guide proper treatment to the cancer affected patient. Health care data analysis comprises enormous data with diversity of health information. One among the most important points that pull down the practitioner’s confidence is that utility of latest software and most sophisticated computing machines. This put them in to the state of confusion for proper and elegant decision making for treating the cancer affected patients. Problems in user interaction, lack of awareness in data mining, improper knowledge in electronic guidelines makes physicians to work with old methods of treatment. Traditional medical practicing and modern methods of computing do not match either because of ignorance. IDA and HMS have significant impact for cancer treatment with speedy diagnosis and faster recovery. This also shows great impact on costs, clinical outcomes and proper guidelines for clinical approach. The prime motto of this survey article is to analyze the survey application, bring out the importance of comparison strategies of IDA to improve decision making for medical practitioner for effective cancer treatment.  

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