Titlebook: Handbook of Large-Scale Distributed Computing in Smart Healthcare; Samee U. Khan,Albert Y. Zomaya,Assad Abbas Book 2017 Springer Internati

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Process Streaming Healthcare Data with Adaptive MapReduce Frameworkr the health status of a physical body. It is very challenging to process, analyze and monitor the streaming data in real time. Therefore, an efficient cloud platform with very elastic scaling capacity is needed to support such kind of real-time streaming data applications. The state-of-art cloud pl

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High-Performance Monte Carlo Simulations for Photon Migration and Applications in Optical Brain Funcain functions and diagnosing brain diseases. However, given the complexity of the human brain anatomy, quantitative analysis of optical brain imaging data has been challenging due to the extensive computation needed to solve the generalized models. In this chapter, we discuss Monte Carlo eXtreme (MC

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Electronic Health Records: Benefits and Challenges for Data Qualityability and standards to large-scale health Database Management Systems (DBMS). In addition, EHR technology provides portfolio management systems that allow Health Care Organisations (HCOs) to deliver higher quality of care to their patients than possible with paper-based records. The EHRs are in hi

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Large Scale Medical Data Mining for Accurate Diagnosis: A Blueprintsis process/decision making on large scale of diseases. Advanced data mining techniques in diseases information processing context become essential. The present study covered several aspects of large scale knowledge mining for medical and diseases investigation. A genome-wide association study was r

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Machine Learning Models for Multidimensional Clinical Dataes include clinical observations, continuous waveforms, lab results, medical images and text notes. The key clinical challenge is to interpret these in a way that helps to improve the standard of patient care. However, the size and complexity of the data sets, which are often multidimensional and dy

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Data Quality in Mobile Sensing Datasets for Pervasive Healthcaredata-driven approach has the potential to become a major tool in the field of epidemiology, aimed at determining the causes of disease in populations, as well as motivating behavior change. These sensing technologies are generating large datasets that demand significant processing and data managemen

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