A Proposed Integrated Approach for BI and GIS in Health Sector to Support Decision Makers (BIGIS-DSS)

Sultan, Torky I.; Nasr, Mona; Khedr, Ayman E.; Abdou, Randa

doi:10.14569/ijacsa.2013.040127

Cited by 3 publications

(1 citation statement)

References 13 publications

(5 reference statements)

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“…It provides multidimensional, summarized views of business data and is used for reporting, analysis, modeling and planning for optimizing the business . [23] OLAP techniques and tools can be used to work with data warehouses or data marts designed for sophisticated enterprise intelligence systems. These systems process queries required to discover trends and analyze critical factors.…”

Section: The Main Components Of Business Intelligencementioning

confidence: 99%

A Proposed Framework for Detecting and Predicting Diseases through Business Intelligence Applications

Ahmed¹,

Seddawy²,

Nasr³

2019

IJANA

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The Demand for healthcare IT and its analytics increases in the last few years. To improve quality of care (e.g., ensuring that patients receive the correct medication) which will help to improve the efficiency of clinical quality and safety, operations.The Nature of the medical field is rich with information where there's a variety and abundance of data but untapped in a correct and effective manner to get the right knowledge. and therefore, the most serious challenge facing this area is the quality of service provided which means to make the diagnose in a proper manner at a timely manner and provide appropriate medications to patients because Poor diagnosing can lead to serious consequences which are unacceptable. And because there is a lack of effective analysis tools to discover hidden relationships and trends in data, so Health information technology has emerged as a new technology in health care sector in a short period by utilizing Business Intelligence 'BI' which is a data-driven Decision Support System. Which Was developed from 1990s to now, and gradually become one of the most important information systems applied in any sector. BI enables to deal with huge amount of data and extract useful knowledge to support decision making. Data mining 'DM' is a kind of data processing technology which can be regarded as a part of the BI system, but it can be also considered as an independent and integrated technology which can treat mass data and extract hidden relationships from it.This introduction highlights the main importance of how to apply the business intelligence applications using data mining techniques to help medical professionals in healthcare sector rapidly diagnosing and predicting diseases of any patients not only this but also detecting the disease complications on the patient which will decrease the overall cost of expenditure that the country paid, briefly this is the central research idea which address the motivation for doing this research.

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Section: The Main Components Of Business Intelligencementioning

confidence: 99%

A Proposed Framework for Detecting and Predicting Diseases through Business Intelligence Applications

Ahmed¹,

Seddawy²,

Nasr³

2019

IJANA

Self Cite

View full text Add to dashboard Cite

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Towards Interactive Visualization of Time Series Data to Support Knowledge Discovery

Géryk

2015

Progress in Artificial Intelligence

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Automated Ham-Spam Lexicon Generation Based on Semantic Relations Extraction

Khedr

Idrees

Shaaban

2020

International Journal of E-Collaboration

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One of the current essential methods for communication is electronic email (e-mail). It is currently considered the official method for different business activities such as conducting agreements, the setup of official meetings, and team collaboration. This continuous interest in e-mails as a communication channel has drawn the attention to the need for eliminating spam which have a vital effect on both network resources and business activities. This research focuses on generating a ham-spam lexicon based on text analysis which is aimed to be one of the main resources for detecting personal spam e-mails. The lexicon generation is a key step to efficiently and economically successful spam elimination. The proposed framework has proven its applicability on a dataset of six groups and the classification algorithms have been examined to prove the efficient classification. The research is a step in a wider view for general intelligent business communication and collaboration framework.

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A Proposed Integrated Approach for BI and GIS in Health Sector to Support Decision Makers (BIGIS-DSS)

Cited by 3 publications

References 13 publications

A Proposed Framework for Detecting and Predicting Diseases through Business Intelligence Applications

A Proposed Framework for Detecting and Predicting Diseases through Business Intelligence Applications

Towards Interactive Visualization of Time Series Data to Support Knowledge Discovery

Automated Ham-Spam Lexicon Generation Based on Semantic Relations Extraction

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