Results 131 to 140 of about 55,056 (264)

Lifespan Pancreas Morphology for Control Versus Type 2 Diabetes Using AI on Largescale Clinical Imaging

open access: yesClinical Anatomy, EarlyView.
ABSTRACT Understanding how pancreas size and shape change with normal aging is critical for establishing a baseline to detect deviations in type 2 diabetes and other pancreatic disease. We measure pancreas size and shape using morphological measurements from early development through aging (ages 0–90).
Lucas W. Remedios   +13 more
wiley   +1 more source

A Graph‐Based Generative Artificial Intelligence Methodology for Autocorrection of Utility‐System P&IDs

open access: yesChemie Ingenieur Technik, EarlyView.
This work explores generative AI for automated revision of Piping and Instrumentation Diagrams (P&IDs). We frame P&ID correction as a translation problem, converting attributed P&ID graphs into sequences and learning revisions with a transformer‐based model.
Lukas Schulze Balhorn   +5 more
wiley   +1 more source

An EEG-Based Edge-AI Framework for Alzheimer's and Creutzfeldt-Jakob Disease Classification. [PDF]

open access: yesSensors (Basel)
Suffian M   +5 more
europepmc   +1 more source

DinoFlow: Self‐supervised pretraining in flow cytometry enables accurate detection of common hematopathological disorders

open access: yesCytometry Part B: Clinical Cytometry, EarlyView.
Abstract Flow cytometry is an essential component of routine hematological lab testing. Many computational methods have been proposed for the analysis of flow cytometry data, but most have focused on supervised learning for just one or a few specific disorders.
Brendan O'Fallon   +4 more
wiley   +1 more source

EventFlow: Real‐time neuromorphic event‐driven classification of two‐phase boiling flow regimes

open access: yesDroplet, EarlyView.
We present a real‐time flow regime classification framework that integrates neuromorphic event‐driven sensing with deep recurrent neural networks. Unlike traditional frame‐based approaches, our system captures sparse event streams from an event‐based camera, representing only the dynamic brightness changes at the individual pixel level.
Sanghyeon Chang   +9 more
wiley   +1 more source

Dynamic geo‐hydrogeological monitoring‐driven situational awareness for real‐time floor water inrush risk prediction in deep mining

open access: yesDeep Underground Science and Engineering, EarlyView.
The fused data extracted from the distributed monitoring system as the data basis, combined with dynamic geological data, are imported into a deep learning model. As the geological conditions of mining and excavation change, the risk of water inrush at the working face is retrieved in real time.
Yongjie Li   +4 more
wiley   +1 more source

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