Potentially malignant oral lesions are visible mucosal changes with risk of progressing to squamous cell carcinoma. These lesions are currently graded as no, mild, moderate, or severe dysplasia per WHO guidelines. While widely used,…
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Among the medical specialties, dermatology has witnessed some of the most promising AI applications in recent years.
By John Halamka, M.D., Diercks President, Mayo Clinic Platform, Nneka Comfere, MD, Division Chair of Dermatopathology and Medical…
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Medical image segmentation is vital for accurate diagnosis. While U-Net-based models are effective, they struggle to capture long-range dependencies in complex anatomy. We propose GH-UNet, a Group-wise Hybrid Convolution-ViT model within the U-Net framework,…
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Imaging is crucial to assess disease extent, activity, and outcomes in inflammatory bowel disease (IBD). Artificial intelligence (AI) image interpretation requires automated exploitation of studies at scale as an initial step. Here we evaluate…
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This study proposes a semi-weakly supervised learning approach for pulmonary embolism (PE) detection on CT pulmonary angiography (CTPA) to alleviate the resource-intensive burden of exhaustive medical image annotation. Attention-based CNN-RNN models were trained on…
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Image by jcomp on Freepik
What You Should Know:
– A team of researchers at the intersection of medicine and technology has harnessed the power of artificial intelligence (AI) and NVIDIA GPUs to develop a new…
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Estimating progression of acute ischemic brain lesions – or biological lesion age – holds huge practical importance for hyperacute stroke management. The current best method for determining lesion age from non-contrast computerised tomography (NCCT),…
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UnitedHealthcare CEO Brian Thompson
Photo: Courtesy UnitedHealth Group
Walking toward the New York Hilton Hotel in Midtown Manhattan this morning, UnitedHealthcare CEO Brian Thompson was fatally shot in what law enforcement officers have called a targeted…
Ex vivo lung perfusion (EVLP) enables advanced assessment of human lungs for transplant suitability. We developed a convolutional neural network (CNN)-based approach to analyze the largest cohort of isolated lung radiographs to date. CNNs…
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By Shania Kennedy
April 02, 2024 – A research team from Arizona State University has developed a machine learning (ML) model capable of predicting whether a patient’s immune system will recognize pathogens and other foreign cells,…
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