PURPOSE: Myocardial computed tomography (CT) late enhancement (LE) allows assessment of myocardial scarring. Super-resolution deep learning image reconstruction (SR-DLR) trained on data acquired from ultra-high-resolution CT may improve image quality...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Mar 12, 2025
Artificial intelligence (AI) has shown great promise in analyzing nasal endoscopic images for disease detection. However, current AI systems require extensive expert-labeled data for each specific medical condition, limiting their applications. In th...
Histopathological image classification using deep learning is crucial for accurate and efficient cancer diagnosis. However, annotating a large amount of histopathological images for training is costly and time-consuming, leading to a scarcity of avai...
BACKGROUND: Intracranial aneurysm rupture is associated with high mortality and disability rates. Early detection is crucial, but increasing diagnostic workloads place significant strain on radiologists. We evaluated the efficacy of a deep learning a...
Recent developments in artificial intelligence (AI) have seen a proliferation of algorithms that are now capable of predicting a range of systemic diseases from retinal images. Unlike traditional retinal disease detection AI models which are trained ...
The lightning development of artificial intelligence (AI) has revolutionized healthcare, helping significant improvements in various applications. This paper provides a comprehensive review of foundation models in healthcare, highlighting their trans...
The widespread adoption of deep learning to model neural activity often relies on "black-box" approaches that lack an interpretable connection between neural activity and network parameters. Here, we propose using algorithm unrolling, a method for in...
We use a combination of Brownian dynamics (BD) simulation results and deep learning (DL) strategies for the rapid identification of large structural changes caused by missense mutations in intrinsically disordered proteins (IDPs). We used ∼6500 IDP s...
With the increasing development of metaverse and human-computer interaction (HMI) technologies, artificial intelligence (AI) applications in virtual reality (VR) environments are receiving significant attention. This study presents a self-sensing fac...
Model-agnostic meta-learning (MAML), coupled with digital twins, is transformative for predictive maintenance (PdM), especially in robotic arms in assembly lines, where rapid and accurate fault classification of arms is essential. Despite gaining sig...
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