Deploying artificial intelligence in the detection of adult appendicular and pelvic fractures in the Singapore emergency department after hours: efficacy, cost savings and non-monetary benefits
Introduction: Radiology plays an integral role in fracture detection in the emergency department (ED). After hours, when there are fewer reporting radiologists, most radiographs are interpreted by ED physicians. A minority of these interpretations may miss diagnoses, which later require the callback...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wolters Kluwer – Medknow Publications
2025-04-01
|
| Series: | Singapore Medical Journal |
| Subjects: | |
| Online Access: | https://journals.lww.com/10.4103/singaporemedj.SMJ-2023-170 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850193652574322688 |
|---|---|
| author | John Jian Xian Quek Oliver James Nickalls Bak Siew Steven Wong Min On Tan |
| author_facet | John Jian Xian Quek Oliver James Nickalls Bak Siew Steven Wong Min On Tan |
| author_sort | John Jian Xian Quek |
| collection | DOAJ |
| description | Introduction:
Radiology plays an integral role in fracture detection in the emergency department (ED). After hours, when there are fewer reporting radiologists, most radiographs are interpreted by ED physicians. A minority of these interpretations may miss diagnoses, which later require the callback of patients for further management. Artificial intelligence (AI) has been viewed as a potential solution to augment the shortage of radiologists after hours. We explored the efficacy of an AI solution in the detection of appendicular and pelvic fractures for adult radiographs performed after hours at a general hospital ED in Singapore, and estimated the potential monetary and non-monetary benefits.
Methods:
One hundred and fifty anonymised abnormal radiographs were retrospectively collected and fed through an AI fracture detection solution. The radiographs were re-read by two radiologist reviewers and their consensus was established as the reference standard. Cases were stratified based on the concordance between the AI solution and the reviewers’ findings. Discordant cases were further analysed based on the nature of the discrepancy into overcall and undercall subgroups. Statistical analysis was performed to evaluate the accuracy, sensitivity and inter-rater reliability of the AI solution.
Results:
Ninety-two examinations were included in the final study radiograph set. The AI solution had a sensitivity of 98.9%, an accuracy of 85.9% and an almost perfect agreement with the reference standard.
Conclusion:
An AI fracture detection solution has similar sensitivity to human radiologists in the detection of fractures on ED appendicular and pelvic radiographs. Its implementation offers significant potential measurable cost, manpower and time savings. |
| format | Article |
| id | doaj-art-fdcdc36a5ab04e159f3f94a1ac8452be |
| institution | OA Journals |
| issn | 0037-5675 2737-5935 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Wolters Kluwer – Medknow Publications |
| record_format | Article |
| series | Singapore Medical Journal |
| spelling | doaj-art-fdcdc36a5ab04e159f3f94a1ac8452be2025-08-20T02:14:11ZengWolters Kluwer – Medknow PublicationsSingapore Medical Journal0037-56752737-59352025-04-0166420220710.4103/singaporemedj.SMJ-2023-170Deploying artificial intelligence in the detection of adult appendicular and pelvic fractures in the Singapore emergency department after hours: efficacy, cost savings and non-monetary benefitsJohn Jian Xian QuekOliver James NickallsBak Siew Steven WongMin On TanIntroduction: Radiology plays an integral role in fracture detection in the emergency department (ED). After hours, when there are fewer reporting radiologists, most radiographs are interpreted by ED physicians. A minority of these interpretations may miss diagnoses, which later require the callback of patients for further management. Artificial intelligence (AI) has been viewed as a potential solution to augment the shortage of radiologists after hours. We explored the efficacy of an AI solution in the detection of appendicular and pelvic fractures for adult radiographs performed after hours at a general hospital ED in Singapore, and estimated the potential monetary and non-monetary benefits. Methods: One hundred and fifty anonymised abnormal radiographs were retrospectively collected and fed through an AI fracture detection solution. The radiographs were re-read by two radiologist reviewers and their consensus was established as the reference standard. Cases were stratified based on the concordance between the AI solution and the reviewers’ findings. Discordant cases were further analysed based on the nature of the discrepancy into overcall and undercall subgroups. Statistical analysis was performed to evaluate the accuracy, sensitivity and inter-rater reliability of the AI solution. Results: Ninety-two examinations were included in the final study radiograph set. The AI solution had a sensitivity of 98.9%, an accuracy of 85.9% and an almost perfect agreement with the reference standard. Conclusion: An AI fracture detection solution has similar sensitivity to human radiologists in the detection of fractures on ED appendicular and pelvic radiographs. Its implementation offers significant potential measurable cost, manpower and time savings.https://journals.lww.com/10.4103/singaporemedj.SMJ-2023-170artificial intelligenceemergency departmentfracturesradiographyradiology |
| spellingShingle | John Jian Xian Quek Oliver James Nickalls Bak Siew Steven Wong Min On Tan Deploying artificial intelligence in the detection of adult appendicular and pelvic fractures in the Singapore emergency department after hours: efficacy, cost savings and non-monetary benefits Singapore Medical Journal artificial intelligence emergency department fractures radiography radiology |
| title | Deploying artificial intelligence in the detection of adult appendicular and pelvic fractures in the Singapore emergency department after hours: efficacy, cost savings and non-monetary benefits |
| title_full | Deploying artificial intelligence in the detection of adult appendicular and pelvic fractures in the Singapore emergency department after hours: efficacy, cost savings and non-monetary benefits |
| title_fullStr | Deploying artificial intelligence in the detection of adult appendicular and pelvic fractures in the Singapore emergency department after hours: efficacy, cost savings and non-monetary benefits |
| title_full_unstemmed | Deploying artificial intelligence in the detection of adult appendicular and pelvic fractures in the Singapore emergency department after hours: efficacy, cost savings and non-monetary benefits |
| title_short | Deploying artificial intelligence in the detection of adult appendicular and pelvic fractures in the Singapore emergency department after hours: efficacy, cost savings and non-monetary benefits |
| title_sort | deploying artificial intelligence in the detection of adult appendicular and pelvic fractures in the singapore emergency department after hours efficacy cost savings and non monetary benefits |
| topic | artificial intelligence emergency department fractures radiography radiology |
| url | https://journals.lww.com/10.4103/singaporemedj.SMJ-2023-170 |
| work_keys_str_mv | AT johnjianxianquek deployingartificialintelligenceinthedetectionofadultappendicularandpelvicfracturesinthesingaporeemergencydepartmentafterhoursefficacycostsavingsandnonmonetarybenefits AT oliverjamesnickalls deployingartificialintelligenceinthedetectionofadultappendicularandpelvicfracturesinthesingaporeemergencydepartmentafterhoursefficacycostsavingsandnonmonetarybenefits AT baksiewstevenwong deployingartificialintelligenceinthedetectionofadultappendicularandpelvicfracturesinthesingaporeemergencydepartmentafterhoursefficacycostsavingsandnonmonetarybenefits AT minontan deployingartificialintelligenceinthedetectionofadultappendicularandpelvicfracturesinthesingaporeemergencydepartmentafterhoursefficacycostsavingsandnonmonetarybenefits |