Value assessment of artificial intelligence in medical imaging: a scoping review
Abstract Background Artificial intelligence (AI) is seen as one of the major disrupting forces in the future healthcare system. However, the assessment of the value of these new technologies is still unclear, and no agreed international health technology assessment-based guideline exists. This study...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-10-01
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| Series: | BMC Medical Imaging |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12880-022-00918-y |
| _version_ | 1797984644347461632 |
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| author | Iben Fasterholdt Mohammad Naghavi-Behzad Benjamin S. B. Rasmussen Tue Kjølhede Mette Maria Skjøth Malene Grubbe Hildebrandt Kristian Kidholm |
| author_facet | Iben Fasterholdt Mohammad Naghavi-Behzad Benjamin S. B. Rasmussen Tue Kjølhede Mette Maria Skjøth Malene Grubbe Hildebrandt Kristian Kidholm |
| author_sort | Iben Fasterholdt |
| collection | DOAJ |
| description | Abstract Background Artificial intelligence (AI) is seen as one of the major disrupting forces in the future healthcare system. However, the assessment of the value of these new technologies is still unclear, and no agreed international health technology assessment-based guideline exists. This study provides an overview of the available literature in the value assessment of AI in the field of medical imaging. Methods We performed a systematic scoping review of published studies between January 2016 and September 2020 using 10 databases (Medline, Scopus, ProQuest, Google Scholar, and six related databases of grey literature). Information about the context (country, clinical area, and type of study) and mentioned domains with specific outcomes and items were extracted. An existing domain classification, from a European assessment framework, was used as a point of departure, and extracted data were grouped into domains and content analysis of data was performed covering predetermined themes. Results Seventy-nine studies were included out of 5890 identified articles. An additional seven studies were identified by searching reference lists, and the analysis was performed on 86 included studies. Eleven domains were identified: (1) health problem and current use of technology, (2) technology aspects, (3) safety assessment, (4) clinical effectiveness, (5) economics, (6) ethical analysis, (7) organisational aspects, (8) patients and social aspects, (9) legal aspects, (10) development of AI algorithm, performance metrics and validation, and (11) other aspects. The frequency of mentioning a domain varied from 20 to 78% within the included papers. Only 15/86 studies were actual assessments of AI technologies. The majority of data were statements from reviews or papers voicing future needs or challenges of AI research, i.e. not actual outcomes of evaluations. Conclusions This review regarding value assessment of AI in medical imaging yielded 86 studies including 11 identified domains. The domain classification based on European assessment framework proved useful and current analysis added one new domain. Included studies had a broad range of essential domains about addressing AI technologies highlighting the importance of domains related to legal and ethical aspects. |
| first_indexed | 2024-04-11T07:06:12Z |
| format | Article |
| id | doaj.art-e87cac759714447b99da03bfe6af9870 |
| institution | Directory Open Access Journal |
| issn | 1471-2342 |
| language | English |
| last_indexed | 2024-04-11T07:06:12Z |
| publishDate | 2022-10-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Imaging |
| spelling | doaj.art-e87cac759714447b99da03bfe6af98702022-12-22T04:38:23ZengBMCBMC Medical Imaging1471-23422022-10-0122111110.1186/s12880-022-00918-yValue assessment of artificial intelligence in medical imaging: a scoping reviewIben Fasterholdt0Mohammad Naghavi-Behzad1Benjamin S. B. Rasmussen2Tue Kjølhede3Mette Maria Skjøth4Malene Grubbe Hildebrandt5Kristian Kidholm6CIMT – Centre for Innovative Medical Technology, Odense University HospitalDepartment of Clinical Research, University of Southern DenmarkDepartment of Clinical Research, University of Southern DenmarkCIMT – Centre for Innovative Medical Technology, Odense University HospitalDepartment of Dermatology and Allergy Centre, Odense University HospitalCIMT – Centre for Innovative Medical Technology, Odense University HospitalCIMT – Centre for Innovative Medical Technology, Odense University HospitalAbstract Background Artificial intelligence (AI) is seen as one of the major disrupting forces in the future healthcare system. However, the assessment of the value of these new technologies is still unclear, and no agreed international health technology assessment-based guideline exists. This study provides an overview of the available literature in the value assessment of AI in the field of medical imaging. Methods We performed a systematic scoping review of published studies between January 2016 and September 2020 using 10 databases (Medline, Scopus, ProQuest, Google Scholar, and six related databases of grey literature). Information about the context (country, clinical area, and type of study) and mentioned domains with specific outcomes and items were extracted. An existing domain classification, from a European assessment framework, was used as a point of departure, and extracted data were grouped into domains and content analysis of data was performed covering predetermined themes. Results Seventy-nine studies were included out of 5890 identified articles. An additional seven studies were identified by searching reference lists, and the analysis was performed on 86 included studies. Eleven domains were identified: (1) health problem and current use of technology, (2) technology aspects, (3) safety assessment, (4) clinical effectiveness, (5) economics, (6) ethical analysis, (7) organisational aspects, (8) patients and social aspects, (9) legal aspects, (10) development of AI algorithm, performance metrics and validation, and (11) other aspects. The frequency of mentioning a domain varied from 20 to 78% within the included papers. Only 15/86 studies were actual assessments of AI technologies. The majority of data were statements from reviews or papers voicing future needs or challenges of AI research, i.e. not actual outcomes of evaluations. Conclusions This review regarding value assessment of AI in medical imaging yielded 86 studies including 11 identified domains. The domain classification based on European assessment framework proved useful and current analysis added one new domain. Included studies had a broad range of essential domains about addressing AI technologies highlighting the importance of domains related to legal and ethical aspects.https://doi.org/10.1186/s12880-022-00918-yScoping reviewValue assessmentEvaluationArtificial intelligenceMedical imaging |
| spellingShingle | Iben Fasterholdt Mohammad Naghavi-Behzad Benjamin S. B. Rasmussen Tue Kjølhede Mette Maria Skjøth Malene Grubbe Hildebrandt Kristian Kidholm Value assessment of artificial intelligence in medical imaging: a scoping review BMC Medical Imaging Scoping review Value assessment Evaluation Artificial intelligence Medical imaging |
| title | Value assessment of artificial intelligence in medical imaging: a scoping review |
| title_full | Value assessment of artificial intelligence in medical imaging: a scoping review |
| title_fullStr | Value assessment of artificial intelligence in medical imaging: a scoping review |
| title_full_unstemmed | Value assessment of artificial intelligence in medical imaging: a scoping review |
| title_short | Value assessment of artificial intelligence in medical imaging: a scoping review |
| title_sort | value assessment of artificial intelligence in medical imaging a scoping review |
| topic | Scoping review Value assessment Evaluation Artificial intelligence Medical imaging |
| url | https://doi.org/10.1186/s12880-022-00918-y |
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