Tag: Artificial intellgence

Three key tips for diabetic foot care (courtesy of GPT-3) #GPT3 ActAgainstAmputation #DiabeticFoot @ALPSlimb @USC @USC_vascular @ResearchatUSC @KeckSchool_USC #ChatBot

Keep your blood sugar levels under control. High blood sugar levels can damage blood vessels and nerves in the feet, increasing the risk of foot problems. Check your feet daily for cuts, blisters, sores, or any other changes. Use a mirror or ask someone else to help you check hard-to-see areas. Wear properly fitting shoes... Continue Reading →

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Development of AI classification model for angiosome-wise interpretive substantiation of plantar feet thermal asymmetry in type 2 diabetic subjects using infrared thermograms #Thermography #ActAgainstAmputation #Diagnostic

From our colleagues in Chennai. Abstract Diabetic Foot Syndrome (DFS) is the prime impetus for most of the lower extremity complications among the diabetic subjects. DFS is characterized by aberrant variations in plantar foot temperature distribution while healthy subjects exhibit a symmetric thermal pattern between the contralateral and ipsilateral plantar feet. Thus, "asymmetry analysis" of... Continue Reading →

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Artificial Intelligence for Predicting and Diagnosing Complications of Diabetes

This from Hong and coworkers under the aegis of David Klonoff. We're pleased to have participated as well. Artificial intelligence can use real-world data to create models capable of making predictions and medical diagnosis for diabetes and its complications. The aim of this commentary article is to provide a general perspective and present recent advances... Continue Reading →

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Individualised risk prediction for improved chronic wound management @USC_Vascular @ResearchatUSC @ALPSlimb #AI #DeepLearning #WoundHealing

This manuscript from our combined team led by Vladica Velickovic exploring deep learning models to improve our diagnostic and therapeutic methods to measure what we manage. Significance Chronic wounds are associated with significant morbidity, marked loss of quality of life and considerable economic burden. Evidence-based risk prediction to guide improved wound prevention and treatment is... Continue Reading →

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Automated Detection of Infection in Diabetic Foot Ulcer Images #AI #DeepLearning #MachineLearning #C2SHiPUsing Convolutional Neural Network

More work supporting the ongoing efforts to create a deep learning/AI model to assist in diagnosis of diabetic foot ulcer/wound healing images J Yogapriya 1, Venkatesan Chandran 2, M G Sumithra 3, B Elakkiya 4, A Shamila Ebenezer 5, C Suresh Gnana Dhas 6 A bacterial or bone infection in the feet causes diabetic foot infection (DFI), which results in reddish skin in the wound and... Continue Reading →

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Classification of Diabetic Foot Ulcers Using Class Knowledge Banks #ArtificialIntelligence #DeepLearning #DiabeticFoot #C2SHiP

Intriguing work from Xu and coworkers showing a continued march toward improvement in AI Models. As the input improves, output will follow! Abstract Diabetic foot ulcers (DFUs) are one of the most common complications of diabetes. Identifying the presence of infection and ischemia in DFU is important for ulcer examination and treatment planning. Recently, the... Continue Reading →

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An explainable machine learning model for predicting in‐hospital amputation rate of patients with diabetic foot ulcer

Just published this past week by our collective Chongqing/Singapore/and local LA squad. Diabetic foot ulcer (DFU) is one of the most serious and alarming diabetic complications, which often leads to high amputation rates in diabetic patients. Machine learning is a part of the field of artificial intelligence, which can automatically learn models from data and... Continue Reading →

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