Results 231 to 240 of about 217,340 (350)

Predicting Postresection Colorectal Liver Metastases Recurrence Using Advanced Graph Neural Networks with Explainability and Causal Inference

open access: yesAdvanced Intelligent Systems, EarlyView.
This study introduces a framework that combines graph neural networks with causal inference to forecast recurrence and uncover the clinical and pathological factors driving it. It further provides interpretability, validates risk factors via counterfactual and interventional analyses, and offers evidence‐based insights for treatment planning ...
Jubair Ahmed   +3 more
wiley   +1 more source

Hierarchical Language Models for Semantic Navigation and Manipulation in an Aerial‐Ground Robotic System

open access: yesAdvanced Intelligent Systems, EarlyView.
A hierarchical multimodal framework coupling a large language model for task decomposition and semantic mapping with a fine‐tuned vision‐language model for semantic perception, enhanced by GridMask, is presented. An aerial‐ground robot team exploits the semantic map for global and local planning.
Haokun Liu   +6 more
wiley   +1 more source

Auditory Processing and Speech Sound Disorders: Behavioral and Electrophysiological Findings. [PDF]

open access: yesAudiol Res
Drosos K   +6 more
europepmc   +1 more source

Item-analysis of Japanese monosyllable list for speech discrimination test.

open access: bronze, 1985
Yoshio Takéuchi   +4 more
openalex   +2 more sources

Securing Generative Artificial Intelligence with Parallel Magnetic Tunnel Junction True Randomness

open access: yesAdvanced Intelligent Systems, EarlyView.
True random numbers can protect generative artificial intelligence (GAI) models from attacks. A highly parallel, spin‐transfer torque magnetic tunnel junction‐based system is demonstrated that generates high‐quality, energy‐efficient random numbers.
Youwei Bao, Shuhan Yang, Hyunsoo Yang
wiley   +1 more source

Synthetic Electrocardiogram Spectrogram Generation Using Generative Adversarial Network‐Based Models: A Comparative Study

open access: yesAdvanced Intelligent Systems, EarlyView.
Cardiovascular diseases are leading death causes; electrocardiogram (ECG) analysis is slow, motivating machine learning and deep learning. This study compares deep convolutional generative adversarial network, conditional GAN, and Wasserstein GAN with gradient penalty (WGAN‐GP) for synthetic ECG spectrograms; Fréchet Inception Distance (FID) and ...
Giovanny Barbosa‐Casanova   +3 more
wiley   +1 more source

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