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:GA Terlouw JofCheminfo22 14.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Čartolovni DigitalHealth2023 9.jpeg|240px]]</div>
'''"[[Journal:PIKAChU: A Python-based informatics kit for analyzing chemical units|PIKAChU: A Python-based informatics kit for analyzing chemical units]]"'''
'''"[[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]]"'''


As efforts to computationally describe and simulate the biochemical world become more commonplace, computer programs that are capable of ''in silico'' chemistry play an increasingly important role in biochemical research. While such programs exist, they are often dependency-heavy, difficult to navigate, or not written in [[Python (programming language)|Python]], the programming language of choice for [[Bioinformatics|bioinformaticians]]. Here, we introduce PIKAChU (Python-based Informatics Kit for Analysing CHemical Units), a [[Chemical informatics|cheminformatics]] toolbox with few dependencies implemented in Python. PIKAChU builds comprehensive molecular graphs from simplified molecular-input line-entry system (SMILES) strings, which allow for easy downstream analysis and visualization of molecules. ... ('''[[Journal:PIKAChU: A Python-based informatics kit for analyzing chemical units|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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