MEDICAL DATA ANALYTICS



Medical Data Analytics (MDA) is a global health economics and outcomes research (GHEOR) consulting firm with over two decades of experience specializing in chart study design and implementation for the life-sciences industry

Big data analytics for medical applications
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Big Data is an accumulation of data sets which are abundant and intricate in character. They comprise both structured and unstructured data that evolve abundant, so speedy they are not convenient by classical relational database systems or current analytical tools. Big Data

Study of fuzzy logic in medical data analytics
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Fuzzy logic provides an intelligent periphery for knowledge representation and reasoning to handle inaccuracy, uncertainty, and vagueness. Fuzzy systems have been successfully applied in healthcare due to their ability to infuse human expert knowledge and granular

Privacy preserving medical data analytics using secure multi party computation. An end-to-end use case
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The new era of big data demands high performance computing, since the amount of data published online is growing exponentially. Cloud computing has emerged as a result, providing strong computational power for both individuals and companies. Though cloud

Big data in medical informatics: improving education through visual analytics .
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A continuous effort to improve healthcare education today is currently driven from the need to create competent health professionals able to meet healthcare demands. Limited research reporting how educational data manipulation can help in healthcare education

Implementation of medical data -based big data analytics service
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A review on big data analytics in medical imaging
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Big data analytics in the application of medical image processing plays a vital role. For better healthcare it is necessary for automatic analysis which helps in early diagnosis of diseases. This paper describes the overview of Big Data , the benefits, challenges and models of big

Data Analytics to Solve the Unique Challenges of Astronaut Medical Data
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Page 1. Data Analytics to Solve the Unique Challenges of Astronaut Medical Data Jacqueline Describe morbidity

Enabling Analytics on Sensitive Medical Data with Secure Multi-Party Computation
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While there is a clearneed to apply data analytics in the healthcare sector, this is often difficult because it requires combining sensitive data from multiple data sources. In this paper, we show how the cryptographic technique of secure multi-party computation can

Improving Detection in Managing Health and Medical Care with Data Analytics
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The purpose is to introduce the demand for the quality movement practice in problems associated with public health. We show both the need and application of quality monitoring, especially the need for multivariate quality concepts to reduce the costs of operating public

AUVA-Augmented Reality Empowers Visual Analytics to explore Medical Curriculum Data .
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Medical curriculum data play a key role in the structure and the organization of medical programs in Universities around the world. The effective processing and usage of these data improve the educational environment of medical students. As a consequence, the new

Real-time Analytics for Big Data : Potentials in Data Science and Medical Research
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It can be implemented based on data from online resources of the surface web Google Trends database perfectly fits this purpose Epidemiologist never attempted to carry out real- time or predictive analytics within the context of digital epidemiology and in connection with

What is a Relation between Data Analytics and Medical Diagnostics
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Data Analytics provides various methods and approaches to extract hidden and poten-tially useful knowledge for different purposes. It means that we can use this knowledge for decision support, eg to identify crucial inputs and relations, to predict some future state, to

Evaluation of Big Data Analytics in Medical Science
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In medical science the concept of big data is very important because in the diseases prevention outcome prediction of co-morbidities, mortality and it save the cost of medical treatment it can used. In the evolution of healthcare research and practices the continuously

Medical Big Data Analytics : An Interesting but Challenging Interdisciplinary Field of Study
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Big data and analytics are hot topics in both the Scientific and business press. It is even introducing a new area of research called data science which includes the techniques, tools, technologies, and processes for analyzing big data . Big data in healthcare and

Data Analytics for Improved Decision Making at a Veterans Affairs Medical Center
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This paper reports on a study using data analytics for decision making at a Veterans Affairs (VA) Medical Center in Marion, IL, to improve patient outcomes. The SAIL (Strategic Analytics for Improvement and Learning) reports, released each quarter, are used to extract

Sensor Data Analytics to Complement Sparse and Incomplete Medical Records for Diabetes Disease Management
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Diabetes mellitus is considered one of the main chronic diseases, and uncontrolled diabetes can lead to various complications that trigger other chronic diseases. Disease management for diabetes is therefore important to reduce the total healthcare cost. Unfortunately

Health and Medical Analytics , through Analytical Focus and Contextualization, with New Challenges and Opportunities in the Context of Big Data
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The central methodology here is Geometric Data Analysis, an alternative term for Correspondence Analysis, for analytics of processes and behaviours. The geometry of the factor space expresses semantics and implicit, underlying, relationships between what is

Big medical text analytics : querying, searching and understanding clinical data
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Information Technologies (IT) are experiencing a dramatic change during this decade (2011- 2020) due to many different factors: political factors affecting cybersecurity of critical systems; industrial factors resulting in more digitalized industries; economic factors, as existing

Medical Material Management Support Using Data Mining and Analytics
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We present the application of data mining and analytics to support medical material management. Medical materials considered include medical equipment, drugs and pharmaceuticals, and blood. This paper presents the work performed in two different Office

Observational Medical Outcomes Partnership and Mini-Sentinel Common Data Models and Analytics : A Systematic Data Driven Comparison
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