Artificial intelligence (AI) in biomedical research: discussion on authors’ declaration of AI in their articles title
Abstract Artificial intelligence (AI) and its different approaches, from machine learning to deep learning, are not new. We discuss here about the declaration of AI in the title of those articles dealing with AI. From 1990 to 2021, while AI articles in the PubMed increased from 300 to 59,596, the pe...
Ausführliche Beschreibung
Autor*in: |
Sardanelli, Francesco [verfasserIn] |
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E-Artikel |
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Englisch |
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2023 |
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Anmerkung: |
© The Author(s) 2023 |
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Übergeordnetes Werk: |
Enthalten in: European radiology experimental - [Cham] : Springer International Publishing, 2017, 7(2023), 1 vom: 16. Jan. |
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Übergeordnetes Werk: |
volume:7 ; year:2023 ; number:1 ; day:16 ; month:01 |
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DOI / URN: |
10.1186/s41747-022-00316-7 |
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SPR049070975 |
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10.1186/s41747-022-00316-7 doi (DE-627)SPR049070975 (SPR)s41747-022-00316-7-e DE-627 ger DE-627 rakwb eng Sardanelli, Francesco verfasserin aut Artificial intelligence (AI) in biomedical research: discussion on authors’ declaration of AI in their articles title 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract Artificial intelligence (AI) and its different approaches, from machine learning to deep learning, are not new. We discuss here about the declaration of AI in the title of those articles dealing with AI. From 1990 to 2021, while AI articles in the PubMed increased from 300 to 59,596, the percentage declaring AI in the title describes a U-like-shaped curve: about 30% in early 1990s, less than 13% in 2005–2014, again 30% in 2020–2021. A similar trend was observed for AI in medical imaging. While the initial decline could be due to the establishment of AI methods, the recent increase could be related to the capacity of AI to outperform humans, especially in image recognition, fuelled by the adoption of graphic processing units for general purpose computing. The recent increase may also be due to the relevance of open issues about AI, including the standardisation of methods, explainability of results, and concerns about AI-induced epoch-making transformations: to say “We are using AI” in the title may also reflect these concerns. Artificial intelligence (dpeaa)DE-He213 Big data (dpeaa)DE-He213 Deep learning (dpeaa)DE-He213 Machine learning (dpeaa)DE-He213 Regression analysis (dpeaa)DE-He213 Castiglioni, Isabella aut Colarieti, Anna aut Schiaffino, Simone aut Di Leo, Giovanni (orcid)0000-0003-0954-2634 aut Enthalten in European radiology experimental [Cham] : Springer International Publishing, 2017 7(2023), 1 vom: 16. Jan. (DE-627)898118557 (DE-600)2905812-0 2509-9280 nnns volume:7 year:2023 number:1 day:16 month:01 https://dx.doi.org/10.1186/s41747-022-00316-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2023 1 16 01 |
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10.1186/s41747-022-00316-7 doi (DE-627)SPR049070975 (SPR)s41747-022-00316-7-e DE-627 ger DE-627 rakwb eng Sardanelli, Francesco verfasserin aut Artificial intelligence (AI) in biomedical research: discussion on authors’ declaration of AI in their articles title 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract Artificial intelligence (AI) and its different approaches, from machine learning to deep learning, are not new. We discuss here about the declaration of AI in the title of those articles dealing with AI. From 1990 to 2021, while AI articles in the PubMed increased from 300 to 59,596, the percentage declaring AI in the title describes a U-like-shaped curve: about 30% in early 1990s, less than 13% in 2005–2014, again 30% in 2020–2021. A similar trend was observed for AI in medical imaging. While the initial decline could be due to the establishment of AI methods, the recent increase could be related to the capacity of AI to outperform humans, especially in image recognition, fuelled by the adoption of graphic processing units for general purpose computing. The recent increase may also be due to the relevance of open issues about AI, including the standardisation of methods, explainability of results, and concerns about AI-induced epoch-making transformations: to say “We are using AI” in the title may also reflect these concerns. Artificial intelligence (dpeaa)DE-He213 Big data (dpeaa)DE-He213 Deep learning (dpeaa)DE-He213 Machine learning (dpeaa)DE-He213 Regression analysis (dpeaa)DE-He213 Castiglioni, Isabella aut Colarieti, Anna aut Schiaffino, Simone aut Di Leo, Giovanni (orcid)0000-0003-0954-2634 aut Enthalten in European radiology experimental [Cham] : Springer International Publishing, 2017 7(2023), 1 vom: 16. Jan. (DE-627)898118557 (DE-600)2905812-0 2509-9280 nnns volume:7 year:2023 number:1 day:16 month:01 https://dx.doi.org/10.1186/s41747-022-00316-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2023 1 16 01 |
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10.1186/s41747-022-00316-7 doi (DE-627)SPR049070975 (SPR)s41747-022-00316-7-e DE-627 ger DE-627 rakwb eng Sardanelli, Francesco verfasserin aut Artificial intelligence (AI) in biomedical research: discussion on authors’ declaration of AI in their articles title 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract Artificial intelligence (AI) and its different approaches, from machine learning to deep learning, are not new. We discuss here about the declaration of AI in the title of those articles dealing with AI. From 1990 to 2021, while AI articles in the PubMed increased from 300 to 59,596, the percentage declaring AI in the title describes a U-like-shaped curve: about 30% in early 1990s, less than 13% in 2005–2014, again 30% in 2020–2021. A similar trend was observed for AI in medical imaging. While the initial decline could be due to the establishment of AI methods, the recent increase could be related to the capacity of AI to outperform humans, especially in image recognition, fuelled by the adoption of graphic processing units for general purpose computing. The recent increase may also be due to the relevance of open issues about AI, including the standardisation of methods, explainability of results, and concerns about AI-induced epoch-making transformations: to say “We are using AI” in the title may also reflect these concerns. Artificial intelligence (dpeaa)DE-He213 Big data (dpeaa)DE-He213 Deep learning (dpeaa)DE-He213 Machine learning (dpeaa)DE-He213 Regression analysis (dpeaa)DE-He213 Castiglioni, Isabella aut Colarieti, Anna aut Schiaffino, Simone aut Di Leo, Giovanni (orcid)0000-0003-0954-2634 aut Enthalten in European radiology experimental [Cham] : Springer International Publishing, 2017 7(2023), 1 vom: 16. Jan. (DE-627)898118557 (DE-600)2905812-0 2509-9280 nnns volume:7 year:2023 number:1 day:16 month:01 https://dx.doi.org/10.1186/s41747-022-00316-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2023 1 16 01 |
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10.1186/s41747-022-00316-7 doi (DE-627)SPR049070975 (SPR)s41747-022-00316-7-e DE-627 ger DE-627 rakwb eng Sardanelli, Francesco verfasserin aut Artificial intelligence (AI) in biomedical research: discussion on authors’ declaration of AI in their articles title 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract Artificial intelligence (AI) and its different approaches, from machine learning to deep learning, are not new. We discuss here about the declaration of AI in the title of those articles dealing with AI. From 1990 to 2021, while AI articles in the PubMed increased from 300 to 59,596, the percentage declaring AI in the title describes a U-like-shaped curve: about 30% in early 1990s, less than 13% in 2005–2014, again 30% in 2020–2021. A similar trend was observed for AI in medical imaging. While the initial decline could be due to the establishment of AI methods, the recent increase could be related to the capacity of AI to outperform humans, especially in image recognition, fuelled by the adoption of graphic processing units for general purpose computing. The recent increase may also be due to the relevance of open issues about AI, including the standardisation of methods, explainability of results, and concerns about AI-induced epoch-making transformations: to say “We are using AI” in the title may also reflect these concerns. Artificial intelligence (dpeaa)DE-He213 Big data (dpeaa)DE-He213 Deep learning (dpeaa)DE-He213 Machine learning (dpeaa)DE-He213 Regression analysis (dpeaa)DE-He213 Castiglioni, Isabella aut Colarieti, Anna aut Schiaffino, Simone aut Di Leo, Giovanni (orcid)0000-0003-0954-2634 aut Enthalten in European radiology experimental [Cham] : Springer International Publishing, 2017 7(2023), 1 vom: 16. Jan. (DE-627)898118557 (DE-600)2905812-0 2509-9280 nnns volume:7 year:2023 number:1 day:16 month:01 https://dx.doi.org/10.1186/s41747-022-00316-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2023 1 16 01 |
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10.1186/s41747-022-00316-7 doi (DE-627)SPR049070975 (SPR)s41747-022-00316-7-e DE-627 ger DE-627 rakwb eng Sardanelli, Francesco verfasserin aut Artificial intelligence (AI) in biomedical research: discussion on authors’ declaration of AI in their articles title 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract Artificial intelligence (AI) and its different approaches, from machine learning to deep learning, are not new. We discuss here about the declaration of AI in the title of those articles dealing with AI. From 1990 to 2021, while AI articles in the PubMed increased from 300 to 59,596, the percentage declaring AI in the title describes a U-like-shaped curve: about 30% in early 1990s, less than 13% in 2005–2014, again 30% in 2020–2021. A similar trend was observed for AI in medical imaging. While the initial decline could be due to the establishment of AI methods, the recent increase could be related to the capacity of AI to outperform humans, especially in image recognition, fuelled by the adoption of graphic processing units for general purpose computing. The recent increase may also be due to the relevance of open issues about AI, including the standardisation of methods, explainability of results, and concerns about AI-induced epoch-making transformations: to say “We are using AI” in the title may also reflect these concerns. Artificial intelligence (dpeaa)DE-He213 Big data (dpeaa)DE-He213 Deep learning (dpeaa)DE-He213 Machine learning (dpeaa)DE-He213 Regression analysis (dpeaa)DE-He213 Castiglioni, Isabella aut Colarieti, Anna aut Schiaffino, Simone aut Di Leo, Giovanni (orcid)0000-0003-0954-2634 aut Enthalten in European radiology experimental [Cham] : Springer International Publishing, 2017 7(2023), 1 vom: 16. Jan. (DE-627)898118557 (DE-600)2905812-0 2509-9280 nnns volume:7 year:2023 number:1 day:16 month:01 https://dx.doi.org/10.1186/s41747-022-00316-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2023 1 16 01 |
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Abstract Artificial intelligence (AI) and its different approaches, from machine learning to deep learning, are not new. We discuss here about the declaration of AI in the title of those articles dealing with AI. From 1990 to 2021, while AI articles in the PubMed increased from 300 to 59,596, the percentage declaring AI in the title describes a U-like-shaped curve: about 30% in early 1990s, less than 13% in 2005–2014, again 30% in 2020–2021. A similar trend was observed for AI in medical imaging. While the initial decline could be due to the establishment of AI methods, the recent increase could be related to the capacity of AI to outperform humans, especially in image recognition, fuelled by the adoption of graphic processing units for general purpose computing. The recent increase may also be due to the relevance of open issues about AI, including the standardisation of methods, explainability of results, and concerns about AI-induced epoch-making transformations: to say “We are using AI” in the title may also reflect these concerns. © The Author(s) 2023 |
abstractGer |
Abstract Artificial intelligence (AI) and its different approaches, from machine learning to deep learning, are not new. We discuss here about the declaration of AI in the title of those articles dealing with AI. From 1990 to 2021, while AI articles in the PubMed increased from 300 to 59,596, the percentage declaring AI in the title describes a U-like-shaped curve: about 30% in early 1990s, less than 13% in 2005–2014, again 30% in 2020–2021. A similar trend was observed for AI in medical imaging. While the initial decline could be due to the establishment of AI methods, the recent increase could be related to the capacity of AI to outperform humans, especially in image recognition, fuelled by the adoption of graphic processing units for general purpose computing. The recent increase may also be due to the relevance of open issues about AI, including the standardisation of methods, explainability of results, and concerns about AI-induced epoch-making transformations: to say “We are using AI” in the title may also reflect these concerns. © The Author(s) 2023 |
abstract_unstemmed |
Abstract Artificial intelligence (AI) and its different approaches, from machine learning to deep learning, are not new. We discuss here about the declaration of AI in the title of those articles dealing with AI. From 1990 to 2021, while AI articles in the PubMed increased from 300 to 59,596, the percentage declaring AI in the title describes a U-like-shaped curve: about 30% in early 1990s, less than 13% in 2005–2014, again 30% in 2020–2021. A similar trend was observed for AI in medical imaging. While the initial decline could be due to the establishment of AI methods, the recent increase could be related to the capacity of AI to outperform humans, especially in image recognition, fuelled by the adoption of graphic processing units for general purpose computing. The recent increase may also be due to the relevance of open issues about AI, including the standardisation of methods, explainability of results, and concerns about AI-induced epoch-making transformations: to say “We are using AI” in the title may also reflect these concerns. © The Author(s) 2023 |
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score |
7.398943 |