Difference between revisions of "Template:Article of the week"

From LIMSWiki
Jump to navigationJump to search
(Updated article of the week text)
(Updated article of the week text)
 
(12 intermediate revisions by the same user not shown)
Line 1: Line 1:
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Sbailò npjCompMat22 8.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:The NOMAD Artificial Intelligence Toolkit: Turning materials science data into knowledge and understanding|The NOMAD Artificial Intelligence Toolkit: Turning materials science data into knowledge and understanding]]"'''
'''"[[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]]"'''


We present the Novel Materials Discovery (NOMAD) [[Artificial intelligence|Artificial Intelligence]] (AI) Toolkit, a web-browser-based infrastructure for the interactive AI-based analysis of [[materials science]] data under FAIR (findable, accessible, interoperable, and reusable) data principles. The AI Toolkit readily operates on FAIR data stored in the central server of the NOMAD Archive, the largest database of materials science data worldwide, as well as locally stored, user-owned data. The NOMAD Oasis, a local, stand-alone server can also be used to run the AI Toolkit. By using [[Jupyter Notebook]]s that run in a web-browser, the NOMAD data can be queried and accessed; [[data mining]], [[machine learning]] (ML), and other AI techniques can then be applied to analyze them ... ('''[[Journal:The NOMAD Artificial Intelligence Toolkit: Turning materials science data into knowledge and understanding|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 />
''Recently featured'':
''Recently featured'':
{{flowlist |
{{flowlist |
* [[Journal:Quality control in the clinical biochemistry laboratory: A glance|Quality control in the clinical biochemistry laboratory: A glance]]
* [[Journal:Sigma metrics as a valuable tool for effective analytical performance and quality control planning in the clinical laboratory: A retrospective study|Sigma metrics as a valuable tool for effective analytical performance and quality control planning in the clinical laboratory: A retrospective study]]
* [[Journal:Shared metadata for data-centric materials science|Shared metadata for data-centric materials science]]
* [[Journal:Why do we need food systems informatics? Introduction to this special collection on smart and connected regional food systems|Why do we need food systems informatics? Introduction to this special collection on smart and connected regional food systems]]
* [[Journal:A metabolomics and big data approach to cannabis authenticity (authentomics)|A metabolomics and big data approach to cannabis authenticity (authentomics)]]
* [[Journal:Data management challenges for artificial intelligence in plant and agricultural research|Data management challenges for artificial intelligence in plant and agricultural research]]
}}
}}

Latest 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...)
Recently featured: