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)
(57 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 Hong CancerInnov22 1-1.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Niszczota EconBusRev23 9-2.png|240px]]</div>
'''"[[Journal:Application of informatics in cancer research and clinical practice: Opportunities and challenges|Application of informatics in cancer research and clinical practice: Opportunities and challenges]]"'''
'''"[[Journal:Judgements of research co-created by generative AI: Experimental evidence|Judgements of research co-created by generative AI: Experimental evidence]]"'''


[[Cancer informatics]] has significantly progressed in the big data era. We summarize the application of [[Informatics (academic field)|informatics]] approaches to the [[cancer]] domain from both the informatics perspective (e.g., [[Information management|data management]] and [[Information science|data science]]) and the clinical perspective (e.g., cancer screening, risk assessment, diagnosis, treatment, and prognosis). We discuss various informatics methods and tools that are widely applied in cancer research and practices, such as cancer databases, data standards, terminologies, high-throughput [[omics]] [[data mining]], [[machine learning]] algorithms, [[artificial intelligence]] [[imaging]], and intelligent radiation ... ('''[[Journal:Application of informatics in cancer research and clinical practice: Opportunities and challenges|Full article...]]''')<br />
The introduction of [[ChatGPT]] has fuelled a public debate on the appropriateness of using generative [[artificial intelligence]] (AI) ([[large language model]]s or LLMs) in work, including a debate on how they might be used (and abused) by researchers. In the current work, we test whether delegating parts of the research process to LLMs leads people to distrust researchers and devalues their scientific work. Participants (''N'' = 402) considered a researcher who delegates elements of the research process to a PhD student or LLM and rated three aspects of such delegation. Firstly, they rated whether it is morally appropriate to do so. Secondly, they judged whether—after deciding to delegate the research process—they would trust the scientist (who decided to delegate) to oversee future projects ... ('''[[Journal:Judgements of research co-created by generative AI: Experimental evidence|Full article...]]''')<br />
''Recently featured'':
''Recently featured'':
{{flowlist |
{{flowlist |
* [[Journal:Recommendations for achieving interoperable and shareable medical data in the USA|Recommendations for achieving interoperable and shareable medical data in the USA]]
* [[Journal:Geochemical biodegraded oil classification using a machine learning approach|Geochemical biodegraded oil classification using a machine learning approach]]
* [[Journal:Can a byte improve our bite? An analysis of digital twins in the food industry|Can a byte improve our bite? An analysis of digital twins in the food industry]]
* [[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]]
* [[Journal:Exploration of organic superionic glassy conductors by process and materials informatics with lossless graph database|Exploration of organic superionic glassy conductors by process and materials informatics with lossless graph database]]
* [[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]]
}}
}}

Revision as of 15:26, 20 May 2024

Fig1 Niszczota EconBusRev23 9-2.png

"Judgements of research co-created by generative AI: Experimental evidence"

The introduction of ChatGPT has fuelled a public debate on the appropriateness of using generative artificial intelligence (AI) (large language models or LLMs) in work, including a debate on how they might be used (and abused) by researchers. In the current work, we test whether delegating parts of the research process to LLMs leads people to distrust researchers and devalues their scientific work. Participants (N = 402) considered a researcher who delegates elements of the research process to a PhD student or LLM and rated three aspects of such delegation. Firstly, they rated whether it is morally appropriate to do so. Secondly, they judged whether—after deciding to delegate the research process—they would trust the scientist (who decided to delegate) to oversee future projects ... (Full article...)
Recently featured: