On diabetic foot, wound healing, amputation prevention, and the merger of consumer tech with medical devices
In the realm of medical imaging and diagnostics, the Diabetic Foot Ulcers Grand Challenge (DFUC) 2022 stands out as a potential milemarker. Spearheaded by Moi Hoon Yap and coworkers, this challenge has pushed the boundaries of what's possible in the segmentation of diabetic foot ulcers (DFUs) using deep learning techniques. The challenge not only provided... Continue Reading →
Harnessing AI in Diabetic Foot Disease: A Leap into 3D Imaging Diabetic foot disease (DFD) is a serious complication of diabetes, often leading to lower limb amputations. With the global prevalence of diabetes on the rise, the urgency to improve early detection and management of DFD has never been greater. A recent systematic review by... Continue Reading →
"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 →
Our long-time friends and colleagues from Manchester, led by B. Cassidy et al., have recently contributed an important addition to the existing literature through their study on the application of Artificial Intelligence (AI) in early detection of Diabetic Foot Ulcers (DFUs). Published in Diabetes Research and Clinical Practice, the study outlines a real-world proof-of-concept clinical... Continue Reading →
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 →
From our team led by super student Mark Swerdlow! Mark Swerdlow 1, Jessica Lo 2, David G Armstrong 3 Objective: Evaluate the inter- and intra-rater reliability of a wound assessment tool in iPhone 12 and 13 mini modalities against a validated iPad mini/Structure Sensor configuration. Approach: We assessed a wound measurement application (eKare inSight) for result consistency in patients presenting with wounds.... Continue Reading →
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 →
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 →
Terrific work from Zhang and coworkers Background: Diabetes mellitus (DM) is a chronic disease with hyperglycemia. If not treated in time, it may lead to lower limb amputation. At the initial stage, the detection of diabetes-related foot ulcer (DFU) is very difficult. Deep learning has demonstrated state-of-the-art performance in various fields and has been used to... Continue Reading →
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 →
