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: Ben Li, Elizabeth J. Enichen, Kimia Heydari, Joseph C. Kvedar
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:npj Digital Medicine
Online Access:https://doi.org/10.1038/s41746-025-01613-2
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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.
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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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