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:Tab1 Montoya FrontPharm2020 11.jpg|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Čartolovni DigitalHealth2023 9.jpeg|240px]]</div>
'''"[[Journal:Cannabis contaminants limit pharmacological use of cannabidiol|Cannabis contaminants limit pharmacological use of cannabidiol]]"'''
'''"[[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]]"'''


For nearly a century, [[wikipedia:Cannabis|cannabis]] has been stigmatized and [[wikipedia:Legality of cannabis|criminalized]] across the globe, but in recent years, there has been a growing interest in cannabis due to the therapeutic potential of [[wikipedia:Cannabinoid#Phytocannabinoids|phytocannabinoids]]. With this emerging interest in cannabis, concerns have arisen about the possible [[wikipedia:Contamination|contaminations]] of [[wikipedia:Hemp|hemp]] with [[wikipedia:Pesticide|pesticides]], [[wikipedia:Heavy metals|heavy metals]], microbial [[wikipedia:Pathogen|pathogens]], and [[wikipedia:Carcinogen|carcinogenic]] compounds during the [[wikipedia:Cannabis cultivation|cultivation]], manufacturing, and packaging processes. This is of particular concern for those turning to cannabis for [[wikipedia:Cannabis (drug)|medicinal purposes]], especially those with compromised immune systems. This review aims to provide types of contaminants and examples of cannabis contamination using case studies that elucidate the medical consequences consumers risk when using adulterated cannabis products. ('''[[Journal:Cannabis contaminants limit pharmacological use of cannabidiol|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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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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