Impact of human and artificial intelligence collaboration on workload reduction in medical image interpretation
Abstract Clinicians face increasing workloads in medical imaging interpretation, and artificial intelligence (AI) offers potential relief. This meta-analysis evaluates the impact of human-AI collaboration on image interpretation workload. Four databases were searched for studies comparing reading ti...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-11-01
|
| Series: | npj Digital Medicine |
| Online Access: | https://doi.org/10.1038/s41746-024-01328-w |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846147438485700608 |
|---|---|
| author | Mingyang Chen Yuting Wang Qiankun Wang Jingyi Shi Huike Wang Zichen Ye Peng Xue Youlin Qiao |
| author_facet | Mingyang Chen Yuting Wang Qiankun Wang Jingyi Shi Huike Wang Zichen Ye Peng Xue Youlin Qiao |
| author_sort | Mingyang Chen |
| collection | DOAJ |
| description | Abstract Clinicians face increasing workloads in medical imaging interpretation, and artificial intelligence (AI) offers potential relief. This meta-analysis evaluates the impact of human-AI collaboration on image interpretation workload. Four databases were searched for studies comparing reading time or quantity for image-based disease detection before and after AI integration. The Quality Assessment of Studies of Diagnostic Accuracy was modified to assess risk of bias. Workload reduction and relative diagnostic performance were pooled using random-effects model. Thirty-six studies were included. AI concurrent assistance reduced reading time by 27.20% (95% confidence interval, 18.22%–36.18%). The reading quantity decreased by 44.47% (40.68%–48.26%) and 61.72% (47.92%–75.52%) when AI served as the second reader and pre-screening, respectively. Overall relative sensitivity and specificity are 1.12 (1.09, 1.14) and 1.00 (1.00, 1.01), respectively. Despite these promising results, caution is warranted due to significant heterogeneity and uneven study quality. |
| format | Article |
| id | doaj-art-bb4ce8b67e0f4621bf4be66e31fce095 |
| institution | Kabale University |
| issn | 2398-6352 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Digital Medicine |
| spelling | doaj-art-bb4ce8b67e0f4621bf4be66e31fce0952024-12-01T12:46:06ZengNature Portfolionpj Digital Medicine2398-63522024-11-017111010.1038/s41746-024-01328-wImpact of human and artificial intelligence collaboration on workload reduction in medical image interpretationMingyang Chen0Yuting Wang1Qiankun Wang2Jingyi Shi3Huike Wang4Zichen Ye5Peng Xue6Youlin Qiao7School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical CollegeSchool of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical CollegeSchool of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical CollegeSchool of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical CollegeSchool of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical CollegeSchool of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical CollegeSchool of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical CollegeSchool of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical CollegeAbstract Clinicians face increasing workloads in medical imaging interpretation, and artificial intelligence (AI) offers potential relief. This meta-analysis evaluates the impact of human-AI collaboration on image interpretation workload. Four databases were searched for studies comparing reading time or quantity for image-based disease detection before and after AI integration. The Quality Assessment of Studies of Diagnostic Accuracy was modified to assess risk of bias. Workload reduction and relative diagnostic performance were pooled using random-effects model. Thirty-six studies were included. AI concurrent assistance reduced reading time by 27.20% (95% confidence interval, 18.22%–36.18%). The reading quantity decreased by 44.47% (40.68%–48.26%) and 61.72% (47.92%–75.52%) when AI served as the second reader and pre-screening, respectively. Overall relative sensitivity and specificity are 1.12 (1.09, 1.14) and 1.00 (1.00, 1.01), respectively. Despite these promising results, caution is warranted due to significant heterogeneity and uneven study quality.https://doi.org/10.1038/s41746-024-01328-w |
| spellingShingle | Mingyang Chen Yuting Wang Qiankun Wang Jingyi Shi Huike Wang Zichen Ye Peng Xue Youlin Qiao Impact of human and artificial intelligence collaboration on workload reduction in medical image interpretation npj Digital Medicine |
| title | Impact of human and artificial intelligence collaboration on workload reduction in medical image interpretation |
| title_full | Impact of human and artificial intelligence collaboration on workload reduction in medical image interpretation |
| title_fullStr | Impact of human and artificial intelligence collaboration on workload reduction in medical image interpretation |
| title_full_unstemmed | Impact of human and artificial intelligence collaboration on workload reduction in medical image interpretation |
| title_short | Impact of human and artificial intelligence collaboration on workload reduction in medical image interpretation |
| title_sort | impact of human and artificial intelligence collaboration on workload reduction in medical image interpretation |
| url | https://doi.org/10.1038/s41746-024-01328-w |
| work_keys_str_mv | AT mingyangchen impactofhumanandartificialintelligencecollaborationonworkloadreductioninmedicalimageinterpretation AT yutingwang impactofhumanandartificialintelligencecollaborationonworkloadreductioninmedicalimageinterpretation AT qiankunwang impactofhumanandartificialintelligencecollaborationonworkloadreductioninmedicalimageinterpretation AT jingyishi impactofhumanandartificialintelligencecollaborationonworkloadreductioninmedicalimageinterpretation AT huikewang impactofhumanandartificialintelligencecollaborationonworkloadreductioninmedicalimageinterpretation AT zichenye impactofhumanandartificialintelligencecollaborationonworkloadreductioninmedicalimageinterpretation AT pengxue impactofhumanandartificialintelligencecollaborationonworkloadreductioninmedicalimageinterpretation AT youlinqiao impactofhumanandartificialintelligencecollaborationonworkloadreductioninmedicalimageinterpretation |