The Artificial Intelligence in Digital Radiology: <i>Part 2</i>: Towards an Investigation of <i>acceptance</i> and <i>consensus</i> on the Insiders
<i>Background.</i> The study deals with the introduction of the artificial intelligence in digital radiology. There is a growing interest in this area of scientific research in <i>acceptance</i> and <i>consensus</i> studies involving both insiders and the public,...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-01-01
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| Series: | Healthcare |
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| Online Access: | https://www.mdpi.com/2227-9032/10/1/153 |
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| author | Francesco Di Basilio Gianluca Esposisto Lisa Monoscalco Daniele Giansanti |
| author_facet | Francesco Di Basilio Gianluca Esposisto Lisa Monoscalco Daniele Giansanti |
| author_sort | Francesco Di Basilio |
| collection | DOAJ |
| description | <i>Background.</i> The study deals with the introduction of the artificial intelligence in digital radiology. There is a growing interest in this area of scientific research in <i>acceptance</i> and <i>consensus</i> studies involving both insiders and the public, based on surveys focused mainly on single professionals. <i>Purpose.</i> The goal of the study is to perform a contemporary investigation on the <i>acceptance</i> and the <i>consensus</i> of the three key professional figures approaching in this field of application: (1) Medical specialists in image diagnostics: the medical specialists (MS)s; (2) experts in physical imaging processes: the medical physicists (MP)s; (3) AI designers: specialists of applied sciences (SAS)s. <i>Methods.</i> Participants (MSs = 92: 48 males/44 females, averaged age 37.9; MPs = 91: 43 males/48 females, averaged age 36.1; SAS = 90: 47 males/43 females, averaged age 37.3) were properly recruited based on specific training. An electronic survey was designed and submitted to the participants with a wide range questions starting from the training and background up to the different applications of the AI and the environment of application. <i>Results.</i> The results show that generally, the three professionals show (a) a high degree of encouraging agreement on the introduction of AI both in imaging and in non-imaging applications using both standalone applications and/or <i>mHealth/eHealth</i>, and (b) a different consent on AI use depending on the training background. <i>Conclusions.</i> The study highlights the usefulness of focusing on both the three key professionals and the usefulness of the investigation schemes facing a wide range of issues. The study also suggests the importance of different methods of administration to improve the adhesion and the need to continue these investigations both with federated and specific initiatives. |
| first_indexed | 2024-03-10T01:23:11Z |
| format | Article |
| id | doaj.art-b0801fde136d4cd182fd23897a010c92 |
| institution | Directory Open Access Journal |
| issn | 2227-9032 |
| language | English |
| last_indexed | 2024-03-10T01:23:11Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Healthcare |
| spelling | doaj.art-b0801fde136d4cd182fd23897a010c922023-11-23T13:56:36ZengMDPI AGHealthcare2227-90322022-01-0110115310.3390/healthcare10010153The Artificial Intelligence in Digital Radiology: <i>Part 2</i>: Towards an Investigation of <i>acceptance</i> and <i>consensus</i> on the InsidersFrancesco Di Basilio0Gianluca Esposisto1Lisa Monoscalco2Daniele Giansanti3Facoltà di Medicina e Psicologia, Sapienza University, Piazzale Aldo Moro, 00185 Rome, ItalyFacoltà di Medicina e Psicologia, Sapienza University, Piazzale Aldo Moro, 00185 Rome, ItalyFaculty of Engineering, Tor Vergata University, 00133 Rome, ItalyCentre Tisp, Istituto Superiore di Sanità, 00161 Rome, Italy<i>Background.</i> The study deals with the introduction of the artificial intelligence in digital radiology. There is a growing interest in this area of scientific research in <i>acceptance</i> and <i>consensus</i> studies involving both insiders and the public, based on surveys focused mainly on single professionals. <i>Purpose.</i> The goal of the study is to perform a contemporary investigation on the <i>acceptance</i> and the <i>consensus</i> of the three key professional figures approaching in this field of application: (1) Medical specialists in image diagnostics: the medical specialists (MS)s; (2) experts in physical imaging processes: the medical physicists (MP)s; (3) AI designers: specialists of applied sciences (SAS)s. <i>Methods.</i> Participants (MSs = 92: 48 males/44 females, averaged age 37.9; MPs = 91: 43 males/48 females, averaged age 36.1; SAS = 90: 47 males/43 females, averaged age 37.3) were properly recruited based on specific training. An electronic survey was designed and submitted to the participants with a wide range questions starting from the training and background up to the different applications of the AI and the environment of application. <i>Results.</i> The results show that generally, the three professionals show (a) a high degree of encouraging agreement on the introduction of AI both in imaging and in non-imaging applications using both standalone applications and/or <i>mHealth/eHealth</i>, and (b) a different consent on AI use depending on the training background. <i>Conclusions.</i> The study highlights the usefulness of focusing on both the three key professionals and the usefulness of the investigation schemes facing a wide range of issues. The study also suggests the importance of different methods of administration to improve the adhesion and the need to continue these investigations both with federated and specific initiatives.https://www.mdpi.com/2227-9032/10/1/153e-healthmedical devicesm-healthdigital-radiologypicture archive and communication systemartificial-intelligence |
| spellingShingle | Francesco Di Basilio Gianluca Esposisto Lisa Monoscalco Daniele Giansanti The Artificial Intelligence in Digital Radiology: <i>Part 2</i>: Towards an Investigation of <i>acceptance</i> and <i>consensus</i> on the Insiders Healthcare e-health medical devices m-health digital-radiology picture archive and communication system artificial-intelligence |
| title | The Artificial Intelligence in Digital Radiology: <i>Part 2</i>: Towards an Investigation of <i>acceptance</i> and <i>consensus</i> on the Insiders |
| title_full | The Artificial Intelligence in Digital Radiology: <i>Part 2</i>: Towards an Investigation of <i>acceptance</i> and <i>consensus</i> on the Insiders |
| title_fullStr | The Artificial Intelligence in Digital Radiology: <i>Part 2</i>: Towards an Investigation of <i>acceptance</i> and <i>consensus</i> on the Insiders |
| title_full_unstemmed | The Artificial Intelligence in Digital Radiology: <i>Part 2</i>: Towards an Investigation of <i>acceptance</i> and <i>consensus</i> on the Insiders |
| title_short | The Artificial Intelligence in Digital Radiology: <i>Part 2</i>: Towards an Investigation of <i>acceptance</i> and <i>consensus</i> on the Insiders |
| title_sort | artificial intelligence in digital radiology i part 2 i towards an investigation of i acceptance i and i consensus i on the insiders |
| topic | e-health medical devices m-health digital-radiology picture archive and communication system artificial-intelligence |
| url | https://www.mdpi.com/2227-9032/10/1/153 |
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