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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Elaboudi AdvInBioinfo2018 2018.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Mishra JofNepMedAss23 61-258.png|220px]]</div>
'''"[[Journal:Big data management for healthcare systems: Architecture, requirements, and implementation|Big data management for healthcare systems: Architecture, requirements, and implementation]]"'''
'''"[[Journal:Knowledge of internal quality control for laboratory tests among laboratory personnel working in a biochemistry department of a tertiary care center: A descriptive cross-sectional study|Knowledge of internal quality control for laboratory tests among laboratory personnel working in a biochemistry department of a tertiary care center: A descriptive cross-sectional study]]"'''


The growing amount of data in the healthcare industry has made inevitable the adoption of big data techniques in order to improve the quality of healthcare delivery. Despite the integration of big data processing approaches and platforms in existing [[Information management|data management]] architectures for healthcare systems, these architectures face difficulties in preventing emergency cases. The main contribution of this paper is proposing an extensible big data architecture based on both stream computing and batch computing in order to enhance further the reliability of healthcare systems by generating real-time alerts and making accurate predictions on patient health condition. Based on the proposed architecture, a prototype implementation has been built for healthcare systems in order to generate real-time alerts. The suggested prototype is based on Spark and MongoDB tools. ('''[[Journal:Big data management for healthcare systems: Architecture, requirements, and implementation|Full article...]]''')<br />
The [[clinical laboratory]] holds a central position in patient care, and as such, ensuring accurate [[laboratory]] test results is a necessity. Internal [[quality control]] (QC) ensures day-to-day laboratory consistency. However, unless practiced, the success of laboratory [[quality management system]]s (QMSs) cannot be achieved. This depends on the efforts and commitment of laboratory personnel for its implementation. Hence, the aim of this study was to find out the knowledge of internal QC for laboratory tests among laboratory personnel working in the Department of Biochemistry, B.P. Koirala Institute of Health Sciences (BPKIHS), a tertiary care center ... ('''[[Journal:Knowledge of internal quality control for laboratory tests among laboratory personnel working in a biochemistry department of a tertiary care center: A descriptive cross-sectional study|Full article...]]''')<br />
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Revision as of 18:14, 6 May 2024

Fig1 Mishra JofNepMedAss23 61-258.png

"Knowledge of internal quality control for laboratory tests among laboratory personnel working in a biochemistry department of a tertiary care center: A descriptive cross-sectional study"

The clinical laboratory holds a central position in patient care, and as such, ensuring accurate laboratory test results is a necessity. Internal quality control (QC) ensures day-to-day laboratory consistency. However, unless practiced, the success of laboratory quality management systems (QMSs) cannot be achieved. This depends on the efforts and commitment of laboratory personnel for its implementation. Hence, the aim of this study was to find out the knowledge of internal QC for laboratory tests among laboratory personnel working in the Department of Biochemistry, B.P. Koirala Institute of Health Sciences (BPKIHS), a tertiary care center ... (Full article...)
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