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

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'''[[Hydroinformatics]]''' is the multidisciplinary application of information and decision support systems to address the equitable and efficient management and use of water for many different purposes. Hydroinformatics draws on and integrates hydraulics, hydrology, environmental engineering, and many other disciplines. It sees application at all points in the water cycle, from atmosphere to ocean, and in artificial interventions in that cycle such as urban drainage and water supply systems. It provides support for decision making at all levels, from governance and policy through to management and operations.
'''"[[Journal:Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study|Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study]]"'''


Hydroinformatics also recogniszs the inherently social nature of the problems of water management and of decision making processes, and it includes mechanisms towards understanding the social processes by which technologies are brought into use and how they change the water system. Since the resources to obtain and develop technological solutions affecting water collection, purification, and distribution continue to be concentrated in the hands of the minority, the need to examine these social processes are particularly acute. Hydroinformatics can help tackle problems and tasks such as improving shallow-water flow models, optimizing damn breaks, and constructing bridges across bodies of water. ('''[[Hydroinformatics|Full article...]]''')<br />
This qualitative study aims to present the aspirations, expectations, and critical analysis of the potential for [[artificial intelligence]] (AI) to transform the patient–physician relationship, according to multi-stakeholder insight. This study was conducted from June to December 2021, using an anticipatory ethics approach and sociology of expectations as the theoretical frameworks. It focused mainly on three groups of stakeholders, namely physicians (''n'' = 12), patients (''n'' = 15), and healthcare managers (''n'' = 11), all of whom are directly related to the adoption of AI in medicine (''n'' = 38). In this study, interviews were conducted with 40% of the patients in the sample (15/38), as well as 31% of the physicians (12/38) and 29% of health managers in the sample (11/38) ... ('''[[Journal:Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study|Full article...]]''')<br />
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''Recently featured'':
''Recently featured'': [[Software as a service]], [[Health informatics]], [[Content delivery network]]
{{flowlist |
* [[Journal:Judgements of research co-created by generative AI: Experimental evidence|Judgements of research co-created by generative AI: Experimental evidence]]
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Latest revision as of 15:48, 26 May 2024

Fig1 Čartolovni DigitalHealth2023 9.jpeg

"Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study"

This qualitative study aims to present the aspirations, expectations, and critical analysis of the potential for artificial intelligence (AI) to transform the patient–physician relationship, according to multi-stakeholder insight. This study was conducted from June to December 2021, using an anticipatory ethics approach and sociology of expectations as the theoretical frameworks. It focused mainly on three groups of stakeholders, namely physicians (n = 12), patients (n = 15), and healthcare managers (n = 11), all of whom are directly related to the adoption of AI in medicine (n = 38). In this study, interviews were conducted with 40% of the patients in the sample (15/38), as well as 31% of the physicians (12/38) and 29% of health managers in the sample (11/38) ... (Full article...)
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