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Diabetic foot complications represent a major global health challenge, with a high prevalence among patients with diabetes. A diabetic foot ulcer (DFU) not only affects the patient›s quality of life but also increases the risk for amputation.
Worldwide, a DFU occurs every second, and an amputation occurs every 20 seconds. The limitations of current detection and intervention methods underline the urgent need for innovative solutions.
Recent advances in artificial intelligence (AI) have paved the way for individualized risk prediction models for chronic wound management. These models use deep learning algorithms to analyze clinical data and images, providing personalized treatment plans that may improve healing outcomes and reduce the risk for amputation.
AI-powered tools can also be deployed for the diagnosis of diabetic foot complications. Using image analysis and pattern recognition, AI tools are learning to accurately detect signs of DFUs and other complications, facilitating early and effective intervention. Our group and others have been working not only on imaging devices but also on thermographic tools that — with the help of AI — can create an automated “foot selfie” to predict and prevent problems before they start.
AI’s predictive capabilities are instrumental to its clinical value. By identifying patients at high risk for DFUs, healthcare providers can implement preemptive measures, significantly reducing the likelihood of severe complications.
Although the potential benefits of AI in diabetic foot care are immense, integrating these tools into clinical practice poses challenges. These include ensuring the reliability of AI predictions, addressing data privacy concerns, and training healthcare professionals on the use of AI technologies.
As in so many other areas in our lives, AI holds the promise to revolutionize diabetic foot and limb preservation, offering hope for improved patient outcomes through early detection, precise diagnosis, and personalized care. However, realizing this potential requires ongoing research, development, and collaboration across the medical and technological fields to ensure these innovative solutions can be effectively integrated into standard care practices.
Dr. Armstrong is professor of surgery, Keck School of Medicine of University of Southern California, Los Angeles, California. He has disclosed the following relevant financial relationships: Partially supported by National Institutes of Health; National Institute of Diabetes; Digestive and Kidney Disease Award Number 1R01124789-01A1.
A version of this article first appeared on Medscape.com.
Diabetic foot complications represent a major global health challenge, with a high prevalence among patients with diabetes. A diabetic foot ulcer (DFU) not only affects the patient›s quality of life but also increases the risk for amputation.
Worldwide, a DFU occurs every second, and an amputation occurs every 20 seconds. The limitations of current detection and intervention methods underline the urgent need for innovative solutions.
Recent advances in artificial intelligence (AI) have paved the way for individualized risk prediction models for chronic wound management. These models use deep learning algorithms to analyze clinical data and images, providing personalized treatment plans that may improve healing outcomes and reduce the risk for amputation.
AI-powered tools can also be deployed for the diagnosis of diabetic foot complications. Using image analysis and pattern recognition, AI tools are learning to accurately detect signs of DFUs and other complications, facilitating early and effective intervention. Our group and others have been working not only on imaging devices but also on thermographic tools that — with the help of AI — can create an automated “foot selfie” to predict and prevent problems before they start.
AI’s predictive capabilities are instrumental to its clinical value. By identifying patients at high risk for DFUs, healthcare providers can implement preemptive measures, significantly reducing the likelihood of severe complications.
Although the potential benefits of AI in diabetic foot care are immense, integrating these tools into clinical practice poses challenges. These include ensuring the reliability of AI predictions, addressing data privacy concerns, and training healthcare professionals on the use of AI technologies.
As in so many other areas in our lives, AI holds the promise to revolutionize diabetic foot and limb preservation, offering hope for improved patient outcomes through early detection, precise diagnosis, and personalized care. However, realizing this potential requires ongoing research, development, and collaboration across the medical and technological fields to ensure these innovative solutions can be effectively integrated into standard care practices.
Dr. Armstrong is professor of surgery, Keck School of Medicine of University of Southern California, Los Angeles, California. He has disclosed the following relevant financial relationships: Partially supported by National Institutes of Health; National Institute of Diabetes; Digestive and Kidney Disease Award Number 1R01124789-01A1.
A version of this article first appeared on Medscape.com.
Diabetic foot complications represent a major global health challenge, with a high prevalence among patients with diabetes. A diabetic foot ulcer (DFU) not only affects the patient›s quality of life but also increases the risk for amputation.
Worldwide, a DFU occurs every second, and an amputation occurs every 20 seconds. The limitations of current detection and intervention methods underline the urgent need for innovative solutions.
Recent advances in artificial intelligence (AI) have paved the way for individualized risk prediction models for chronic wound management. These models use deep learning algorithms to analyze clinical data and images, providing personalized treatment plans that may improve healing outcomes and reduce the risk for amputation.
AI-powered tools can also be deployed for the diagnosis of diabetic foot complications. Using image analysis and pattern recognition, AI tools are learning to accurately detect signs of DFUs and other complications, facilitating early and effective intervention. Our group and others have been working not only on imaging devices but also on thermographic tools that — with the help of AI — can create an automated “foot selfie” to predict and prevent problems before they start.
AI’s predictive capabilities are instrumental to its clinical value. By identifying patients at high risk for DFUs, healthcare providers can implement preemptive measures, significantly reducing the likelihood of severe complications.
Although the potential benefits of AI in diabetic foot care are immense, integrating these tools into clinical practice poses challenges. These include ensuring the reliability of AI predictions, addressing data privacy concerns, and training healthcare professionals on the use of AI technologies.
As in so many other areas in our lives, AI holds the promise to revolutionize diabetic foot and limb preservation, offering hope for improved patient outcomes through early detection, precise diagnosis, and personalized care. However, realizing this potential requires ongoing research, development, and collaboration across the medical and technological fields to ensure these innovative solutions can be effectively integrated into standard care practices.
Dr. Armstrong is professor of surgery, Keck School of Medicine of University of Southern California, Los Angeles, California. He has disclosed the following relevant financial relationships: Partially supported by National Institutes of Health; National Institute of Diabetes; Digestive and Kidney Disease Award Number 1R01124789-01A1.
A version of this article first appeared on Medscape.com.
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ARMSTRONG, DPM, MD, PHD</bylineFull> <bylineTitleText/> <USOrGlobal/> <wireDocType/> <newsDocType/> <journalDocType/> <linkLabel/> <pageRange/> <citation/> <quizID/> <indexIssueDate/> <itemClass qcode="ninat:text"/> <provider qcode="provider:imng"> <name>IMNG Medical Media</name> <rightsInfo> <copyrightHolder> <name>Frontline Medical News</name> </copyrightHolder> <copyrightNotice>Copyright (c) 2015 Frontline Medical News, a Frontline Medical Communications Inc. company. All rights reserved. This material may not be published, broadcast, copied, or otherwise reproduced or distributed without the prior written permission of Frontline Medical Communications Inc.</copyrightNotice> </rightsInfo> </provider> <abstract/> <metaDescription>Diabetic foot complications represent a major global health challenge, with a high prevalence among patients with diabetes. A diabetic foot ulcer (DFU) not only</metaDescription> <articlePDF/> <teaserImage/> <teaser>AI uses deep learning algorithms to analyze clinical data and images, providing personalized treatment plans that may improve healing outcomes and reduce the risk for amputation.</teaser> <title>Using AI to Transform Diabetic Foot and Limb Preservation</title> <deck/> <disclaimer/> <AuthorList/> <articleURL/> <doi/> <pubMedID/> <publishXMLStatus/> <publishXMLVersion>1</publishXMLVersion> <useEISSN>0</useEISSN> <urgency/> <pubPubdateYear/> <pubPubdateMonth/> <pubPubdateDay/> <pubVolume/> <pubNumber/> <wireChannels/> <primaryCMSID/> <CMSIDs/> <keywords/> <seeAlsos/> <publications_g> <publicationData> <publicationCode>endo</publicationCode> <pubIssueName/> <pubArticleType/> <pubTopics/> <pubCategories/> <pubSections/> </publicationData> <publicationData> <publicationCode>fp</publicationCode> <pubIssueName/> <pubArticleType/> <pubTopics/> <pubCategories/> <pubSections/> </publicationData> <publicationData> <publicationCode>im</publicationCode> <pubIssueName/> <pubArticleType/> <pubTopics/> <pubCategories/> <pubSections/> </publicationData> </publications_g> <publications> <term canonical="true">34</term> <term>15</term> <term>21</term> </publications> <sections> <term canonical="true">52</term> </sections> <topics> <term>38029</term> <term canonical="true">205</term> </topics> <links/> </header> <itemSet> <newsItem> <itemMeta> <itemRole>Main</itemRole> <itemClass>text</itemClass> <title>Using AI to Transform Diabetic Foot and Limb Preservation</title> <deck/> </itemMeta> <itemContent> <p>Diabetic foot complications represent a major global health challenge, with a <a href="https://doi.org/10.1056/NEJMra1615439">high prevalence</a> among patients with diabetes. A diabetic foot ulcer (DFU) not only affects the patient›s quality of life but also increases the <a href="https://dx.doi.org/10.1001/jama.2023.10578">risk for amputation</a>.</p> <p>Worldwide, a DFU occurs every second, and an amputation occurs every 20 seconds. The limitations of current detection and intervention methods underline the urgent need for innovative solutions.<br/><br/>Recent advances in artificial intelligence (AI) have paved the way for individualized risk prediction models for chronic <a href="https://emedicine.medscape.com/article/194018-overview">wound management</a>. These models use deep learning algorithms to <a href="https://doi.org/10.1177/19322968221124583">analyze clinical data</a> and <a href="https://doi.org/10.1089/wound.2022.0095">images</a>, providing personalized treatment plans that may improve healing outcomes and reduce the risk for amputation.<br/><br/>AI-powered tools can also be deployed for the diagnosis of diabetic foot complications. Using image analysis and pattern recognition, AI tools are learning to accurately <a href="https://doi.org/10.17925/EE.2021.17.1.5">detect</a> signs of DFUs and other complications, facilitating early and effective intervention. Our group and others have been working not only on imaging devices but also on thermographic tools that — with the help of AI — can create an automated <a href="https://doi.org/%20doi:10.1177/19322968211053348">“foot selfie”</a> to predict and prevent problems before they start.<br/><br/>AI’s <a href="https://doi.org/10.1089/wound.2022.0017">predictive capabilities</a> are instrumental to its clinical value. By identifying patients at high risk for DFUs, healthcare providers can implement preemptive measures, significantly reducing the likelihood of severe complications.<br/><br/>Although the potential benefits of AI in diabetic foot care are immense, integrating these tools into clinical practice poses challenges. These include ensuring the reliability of AI predictions, addressing data privacy concerns, and training healthcare professionals on the use of AI technologies.<br/><br/>As in so many other areas in our lives, AI holds the promise to revolutionize diabetic foot and limb preservation, offering hope for improved patient outcomes through early detection, precise diagnosis, and personalized care. However, realizing this potential requires ongoing research, development, and collaboration across the medical and technological fields to ensure these innovative solutions can be effectively integrated into standard care practices.<span class="end"/></p> <p> <em>Dr. Armstrong is professor of surgery, Keck School of Medicine of University of Southern California, Los Angeles, California. He has disclosed the following relevant financial relationships: Partially supported by National Institutes of Health; National Institute of Diabetes; Digestive and Kidney Disease Award Number 1R01124789-01A1.</em> </p> <p> <em>A version of this article first appeared on <span class="Hyperlink"><a href="https://www.medscape.com/viewarticle/using-ai-transform-diabetic-foot-and-limb-preservation-2024a100068w">Medscape.com</a></span>.</em> </p> </itemContent> </newsItem> <newsItem> <itemMeta> <itemRole>teaser</itemRole> <itemClass>text</itemClass> <title/> <deck/> </itemMeta> <itemContent> </itemContent> </newsItem> </itemSet></root>