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)
(279 intermediate revisions by the same user not shown)
Line 1: Line 1:
'''"[[Journal:Laboratory information system – Where are we today?|Laboratory information system – Where are we today?]]"'''
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Tab1 Williamson F1000Res2023 10.png|240px]]</div>
'''"[[Journal:Data management challenges for artificial intelligence in plant and agricultural research|Data management challenges for artificial intelligence in plant and agricultural research]]"'''


Wider implementation of [[laboratory information system]]s (LIS) in [[Clinical laboratory|clinical laboratories]] in Serbia was initiated 10 years ago. The first LIS in the Railway Health Care Institute was implemented nine years ago. Before the LIS was initiated, manual admission procedures limited daily output of patients. Moreover, manual entering of patient data and ordering tests on analyzers was problematic and time-consuming. After completing tests, [[laboratory]] personnel had to write results in a patient register (with potential errors) and provide invoices for health insurance organizations. The first LIS brought forward some advantages with regards to these obstacles, but it also showed various weaknesses. These can be summarized as rigidity of the system and inability to fulfill user expectation. After four years of use, we replaced this system with another LIS. Hence, the main aim of this paper is to evaluate the advantages of using LIS in the Railway Health Care Institute's laboratory and also to discuss further possibilities for its application. ('''[[Journal:Laboratory information system – Where are we today?|Full article...]]''')<br />
[[Artificial intelligence]] (AI) is increasingly used within plant science, yet it is far from being routinely and effectively implemented in this domain. Particularly relevant to the development of novel food and agricultural technologies is the development of validated, meaningful, and usable ways to integrate, compare, and [[Data visualization|visualize]] large, multi-dimensional datasets from different sources and scientific approaches. After a brief summary of the reasons for the interest in data science and AI within plant science, the paper identifies and discusses eight key challenges in [[Information management|data management]] that must be addressed to further unlock the potential of AI in crop and agronomic research, and particularly the application of [[machine learning]] (ML), which holds much promise for this domain ... ('''[[Journal:Data management challenges for artificial intelligence in plant and agricultural research|Full article...]]''')<br />
<br />
''Recently featured'':
''Recently featured'':  
{{flowlist |
: ▪ [[Journal:Clinical note creation, binning, and artificial intelligence|Clinical note creation, binning, and artificial intelligence]]
* [[Journal:A blockchain-driven IoT-based food quality traceability system for dairy products using a deep learning model|A blockchain-driven IoT-based food quality traceability system for dairy products using a deep learning model]]
: ▪ [[Journal:Predicting biomedical metadata in CEDAR: A study of Gene Expression Omnibus (GEO)|Predicting biomedical metadata in CEDAR: A study of Gene Expression Omnibus (GEO)]]
* [[Journal:Effect of good clinical laboratory practices (GCLP) quality training on knowledge, attitude, and practice among laboratory professionals: Quasi-experimental study|Effect of good clinical laboratory practices (GCLP) quality training on knowledge, attitude, and practice among laboratory professionals: Quasi-experimental study]]
: ▪ [[Journal:Rapid development of entity-based data models for bioinformatics with persistence object-oriented design and structured interfaces|Rapid development of entity-based data models for bioinformatics with persistence object-oriented design and structured interfaces]]
* [[Journal:GitHub as an open electronic laboratory notebook for real-time sharing of knowledge and collaboration|GitHub as an open electronic laboratory notebook for real-time sharing of knowledge and collaboration]]
}}

Revision as of 17:50, 15 April 2024

Tab1 Williamson F1000Res2023 10.png

"Data management challenges for artificial intelligence in plant and agricultural research"

Artificial intelligence (AI) is increasingly used within plant science, yet it is far from being routinely and effectively implemented in this domain. Particularly relevant to the development of novel food and agricultural technologies is the development of validated, meaningful, and usable ways to integrate, compare, and visualize large, multi-dimensional datasets from different sources and scientific approaches. After a brief summary of the reasons for the interest in data science and AI within plant science, the paper identifies and discusses eight key challenges in data management that must be addressed to further unlock the potential of AI in crop and agronomic research, and particularly the application of machine learning (ML), which holds much promise for this domain ... (Full article...)
Recently featured:

Retrieved from "https://www.limswiki.org/index.php?title=Template:Article_of_the_week&oldid=63298"