Tag: artificial intelligence

Healing Profiles in Patients with a Chronic Diabetic Foot Ulcer: An Exploratory Study with Machine Learning #AI #ML #DeepLearning #DFU #DiabeticFoot #ActAgainstAmputation

"Healing Profiles in Patients with a Chronic Diabetic Foot Ulcer: An Exploratory Study with Machine Learning" focuses on the complex healing process of diabetic foot ulcers (DFU). It uses machine learning and decision trees to assess healing and prognosis risk profiles in patients. Evaluating various factors, including clinical, biochemical, and psychological aspects, the study identifies... Continue Reading →

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Dolastatin 16: Using Network Pharmacology to Find the Next Promising Diabetic Wound Healing Agent? #DrugDiscovery #DiabeticFoot #ActAgainstAmputation

A recent study published in Springer Link has revealed the potential of Dolastatin 16 as a diabetic wound healing agent[1]. Diabetic foot ulcers are a significant complication of diabetes, and finding effective treatments is crucial to prevent amputations and improve patients' quality of life. In this blog post, we will discuss the findings of this... Continue Reading →

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Would you trust an AI doctor? New research shows patients are split #AI #C2SHiP

bionic hand and human hand finger pointing

Great work from our long-time SALSAmigo, Distinguished Prof. Marv Slepian Artificial intelligence-powered medical treatment options are on the rise and have the potential to improve diagnostic accuracy, but a new study led by University of Arizona Health Sciences researchers found that about 52% of participants would choose a human doctor rather than AI for diagnosis... Continue Reading →

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Simultaneous Segmentation and Classification of Pressure Injury Image Data Using Mask-R-CNN ActAgainstAmputation #DiabeticFoot @ALPSlimb @USC @USC_vascular @ResearchatUSC @KeckSchool_USC #AI #DeepLearning @TheNPIAP

This just published from our SALSA team led by Mark Swerdlow. We're already getting data requests on this one. Building on these models is what it's all about! Mark Swerdlow,1Ozgur Guler,2Raphael Yaakov,2and David G. Armstrong1 Background. Pressure injuries (PIs) impose a substantial burden on patients, caregivers, and healthcare systems, affecting an estimated 3 million Americans and... Continue Reading →

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ACTNet: asymmetric convolutional transformer network for diabetic foot ulcers classification #DeepLearning #DiabeticFoot

More deep learning models for the diabetic foot- this time in image analysis by Ai, Yang and Xi. Most existing image classification methods have achieved significant progress in the field of natural images. However, in the field of diabetic foot ulcer (DFU) where data is scarce and complex, the accurate classification of data is still... Continue Reading →

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A Novel Machine Learning Approach for Severity Classification of Diabetic Foot Complications Using Thermogram Images #ActAgainstAmputation

We are seeing and better approaches to assisting us in identifying subtle asymmetries and personalized discontinuities in thermometry. This work from our Qatari colleagues is just such an example. Diabetes mellitus (DM) is one of the most prevalent diseases in the world, and is correlated to a high index of mortality. One of its major... Continue Reading →

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Transcriptomic Fingerprint of Bacterial Infection in Lower Extremity Ulcers @ALPSLimb #ActAgainstAmputation

Important work from our Danish and Aussie colleagues Abstract Background and purpose: Clinicians and researchers utilize subjective, clinical classification systems to stratify lower extremity ulcer infections for treatment and research. The purpose of this study was to examine whether these clinical classifications are reflected in the ulcer's transcriptome. Methods: RNA-sequencing (RNA-seq) was performed on biopsies from clinically... Continue Reading →

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Development of a prediction model for foot ulcer recurrence in people with diabetes using easy-to-obtain clinical variables #Remission #DiabeticFoot #UlcerFreeDays #Thermometry

Here is important work from our long-time Dutch friends and colleagues. Bottom line: there are now key factors that can be inputted into models to predict (and therefore reduce) risk for reulceration in patients in diabetic foot remission. This is the first multivariate model we've seen include use of personal thermometry. Wouter B Aan de... Continue Reading →

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Toward Machine-Learning-Based Decision Support in Diabetes Care: A Risk Stratification Study on Diabetic Foot Ulcer and Amputation

Great effort from our colleagues in Aarhus and Copenhagen. Diabetes mellitus is associated with serious complications, with foot ulcers and amputation of limbs among the most debilitating consequences of late diagnosis and treatment of foot ulcers. Thus, prediction and on-time treatment of diabetic foot ulcers (DFU) are of great importance for improving and maintaining patients'... Continue Reading →

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