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

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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Buabbas JMIRMedInfo2016 4-2.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Tab1 Williamson F1000Res2023 10.png|240px]]</div>
'''"[[Journal:Users’ perspectives on a picture archiving and communication system (PACS): An in-depth study in a teaching hospital in Kuwait|Users’ perspectives on a picture archiving and communication system (PACS): An in-depth study in a teaching hospital in Kuwait]]"'''
'''"[[Journal:Data management challenges for artificial intelligence in plant and agricultural research|Data management challenges for artificial intelligence in plant and agricultural research]]"'''


The [[picture archiving and communication system]] (PACS) is a well-known [[imaging informatics]] application in health care organizations, specifically designed for the radiology department. Health care providers have exhibited willingness toward evaluating PACS in hospitals to ascertain the critical success and failure of the technology, considering that evaluation is a basic requirement.
[[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 />
 
''Recently featured'':
This study aimed to evaluate the success of a PACS in a regional teaching hospital of Kuwait, from users’ perspectives, using information systems success criteria.
{{flowlist |
 
* [[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]]
An in-depth study was conducted by using quantitative and qualitative methods. This mixed-method study was based on: (1) questionnaires, distributed to all radiologists and technologists and (2) interviews, conducted with PACS administrators. ('''[[Journal:Users’ perspectives on a picture archiving and communication system (PACS): An in-depth study in a teaching hospital in Kuwait|Full article...]]''')<br />
* [[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]]
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* [[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]]
''Recently featured'':  
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: ▪ [[Journal:Effective information extraction framework for heterogeneous clinical reports using online machine learning and controlled vocabularies|Effective information extraction framework for heterogeneous clinical reports using online machine learning and controlled vocabularies]]
: ▪ [[Journal:Selecting a laboratory information management system for biorepositories in low- and middle-income countries: The H3Africa experience and lessons learned|Selecting a laboratory information management system for biorepositories in low- and middle-income countries: The H3Africa experience and lessons learned]]
: ▪ [[Journal:Baobab Laboratory Information Management System: Development of an open-source laboratory information management system for biobanking|Baobab Laboratory Information Management System: Development of an open-source laboratory information management system for biobanking]]

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...)
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