Results 221 to 230 of about 893,776 (343)

Assessing Large Multimodal Models for One‐Shot Learning and Interpretability in Biomedical Image Classification

open access: yesAdvanced Intelligent Systems, EarlyView.
Image classification plays a pivotal role in biomedical image analysis. Herein, it is shown that large multimodal models, such as GPT‐4, achieve superior performance in one‐shot learning, generalization, interpretability, and text‐driven image classification. Applications span tissue, cell type, cellular state, and disease classification, outperforming
Wenpin Hou   +4 more
wiley   +1 more source

Aquaporins in Acute Brain Injury: Insights from Clinical and Experimental Studies. [PDF]

open access: yesBiomedicines
Kokkoris S   +9 more
europepmc   +1 more source

Smart Transfemoral Prosthetic Socket with Motorized Cable‐Driven System

open access: yesAdvanced Intelligent Systems, EarlyView.
This study presents an innovative transfemoral socket featuring a motorized cable‐driven system and a sensorized liner, designed to adapt to changes in residual limb volume while monitoring interface pressures. Users can seamlessly control the socket in both open‐ and closed‐loop modes via a customized mobile application, enhancing comfort and ...
Linda Paternò   +7 more
wiley   +1 more source

Multi‐Disease Detection in Retinal Imaging Using VNet with Image Processing Methods for Data Generation

open access: yesAdvanced Intelligent Systems, EarlyView.
This study introduces a data augmentation method that expands an ophthalmology dataset by 12x, enhancing robustness and reducing overfitting. A novel VNet architecture improves accuracy by 10% over the original dataset and 5% over Grand Challenge benchmarks.
Samad Azimi Abriz   +3 more
wiley   +1 more source

Impact of tumor size and peritumoral edema on outcomes and complications in anterior midline skull base meningiomas. [PDF]

open access: yesBrain Spine
Qasem LE   +11 more
europepmc   +1 more source

RefineCatDiff: Toward High‐Quality Medical Image Segmentation via a Categorical Diffusion Refinement Framework

open access: yesAdvanced Intelligent Systems, EarlyView.
This study proposes RefineCatDiff, a refinement framework for high‐quality medical image segmentation. By developing a categorical distribution‐based discrete diffusion process for refinement, the framework aligns well with the characteristics of image segmentation tasks. Experimental results on multiple datasets across different modalities demonstrate
Feng Liu   +8 more
wiley   +1 more source

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