Artificial intelligence guided imaging as a tool to fill gaps in health care delivery
Deep vein thrombosis (DVT) causes significant morbidity/mortality and timely diagnosis often via ultrasound is critical. However, the shortage of trained ultrasound providers has been an ongoing challenge. Recently, Speranza and colleagues (2025) demonstrated that an artificial intelligence (AI) gui...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-05-01
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| Series: | npj Digital Medicine |
| Online Access: | https://doi.org/10.1038/s41746-025-01613-2 |
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| _version_ | 1850190952544600064 |
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| author | Ben Li Elizabeth J. Enichen Kimia Heydari Joseph C. Kvedar |
| author_facet | Ben Li Elizabeth J. Enichen Kimia Heydari Joseph C. Kvedar |
| author_sort | Ben Li |
| collection | DOAJ |
| description | Deep vein thrombosis (DVT) causes significant morbidity/mortality and timely diagnosis often via ultrasound is critical. However, the shortage of trained ultrasound providers has been an ongoing challenge. Recently, Speranza and colleagues (2025) demonstrated that an artificial intelligence (AI) guided ultrasound system used by non-ultrasound-trained nurses with remote clinician review can achieve sensitivities of 90–98% and specificities of 74–100% for diagnosing DVT. This study highlights the potential for AI guided imaging to address important gaps in health care delivery. |
| format | Article |
| id | doaj-art-5d9da931dbfb4e83a426827fc5c55102 |
| institution | OA Journals |
| issn | 2398-6352 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Digital Medicine |
| spelling | doaj-art-5d9da931dbfb4e83a426827fc5c551022025-08-20T02:15:06ZengNature Portfolionpj Digital Medicine2398-63522025-05-01811210.1038/s41746-025-01613-2Artificial intelligence guided imaging as a tool to fill gaps in health care deliveryBen Li0Elizabeth J. Enichen1Kimia Heydari2Joseph C. Kvedar3Division of Vascular Surgery, University of TorontoHarvard Medical SchoolHarvard Medical SchoolHarvard Medical SchoolDeep vein thrombosis (DVT) causes significant morbidity/mortality and timely diagnosis often via ultrasound is critical. However, the shortage of trained ultrasound providers has been an ongoing challenge. Recently, Speranza and colleagues (2025) demonstrated that an artificial intelligence (AI) guided ultrasound system used by non-ultrasound-trained nurses with remote clinician review can achieve sensitivities of 90–98% and specificities of 74–100% for diagnosing DVT. This study highlights the potential for AI guided imaging to address important gaps in health care delivery.https://doi.org/10.1038/s41746-025-01613-2 |
| spellingShingle | Ben Li Elizabeth J. Enichen Kimia Heydari Joseph C. Kvedar Artificial intelligence guided imaging as a tool to fill gaps in health care delivery npj Digital Medicine |
| title | Artificial intelligence guided imaging as a tool to fill gaps in health care delivery |
| title_full | Artificial intelligence guided imaging as a tool to fill gaps in health care delivery |
| title_fullStr | Artificial intelligence guided imaging as a tool to fill gaps in health care delivery |
| title_full_unstemmed | Artificial intelligence guided imaging as a tool to fill gaps in health care delivery |
| title_short | Artificial intelligence guided imaging as a tool to fill gaps in health care delivery |
| title_sort | artificial intelligence guided imaging as a tool to fill gaps in health care delivery |
| url | https://doi.org/10.1038/s41746-025-01613-2 |
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