Results 251 to 260 of about 3,335,885 (354)

Public Art: A Critical Approach

, 2014
Andrea Baldini
openalex   +1 more source

IAR‐Net: Tabular Deep Learning Model for Interventionalist's Action Recognition

Advanced Intelligent Systems, EarlyView.
This study presents IAR‐Net, a deep‐learning framework for catheterization action recognition. To ensure optimality, this study quantifies interoperator similarities and differences using statistical tests, evaluates the distribution fidelity of synthetic data produced by six generative models, and benchmarks multiple deep‐learning models.
Toluwanimi Akinyemi, Olatunji Omisore, Wenjing Du, Wenke Duan, Chen Bailang, Liu Kun, Lei Wang, Minxin Wei   +7 more
wiley   +1 more source

Assessing the impact of the COVID-19 pandemic on uptake of HIV treatment in Bandung and Yogyakarta, Indonesia: A retrospective cohort study. [PDF]

PLOS Glob Public Health
Mashuri YA, Boettiger D, Negara SNS, Wahyuningtias SD, Probandari A, Liverani M, Wulandari LPL, Ahmad RA, Thabrany H, Fardousi N, Kaldor J, Subronto YW, Wiseman V.   +12 more
europepmc   +1 more source

Women Building History: Public Art at the 1893 Columbian Exposition by Wanda M. Corn

, 2012
Maureen A. Flanagan
openalex   +1 more source

Public Art, Dance, and Music and the Politics of Culture in East and Central Africa

Sam Kasule
openalex   +2 more sources

Roadmap on Artificial Intelligence‐Augmented Additive Manufacturing

Advanced Intelligent Systems, EarlyView.
This Roadmap outlines the transformative role of artificial intelligence‐augmented additive manufacturing, highlighting advances in design, monitoring, and product development. By integrating tools such as generative design, computer vision, digital twins, and closed‐loop control, it presents pathways toward smart, scalable, and autonomous additive ...
Ali Zolfagharian, Liuchao Jin, Qi Ge, Wei‐Hsin Liao, Andrés Díaz Lantada, Francisco Franco Martínez, Tianyu Zhang, Tao Liu, Charlie C. L. Wang, Mohammad Hossein Mosallanejad, Reza Ghanavati, Abdollah Saboori, Alejandro De Blas De Miguel, William Solórzano‐Requejo, Yi Cai, Xiangyang Dong, Huangyi Qu, Najmeh Samadiani, Guangyan Huang, Austin Downey, Yanzhou Fu, Lang Yuan, Tsz‐Kwan (Glory) Lee, Arbind Agrahari Baniya, Eisha Waseem, Abdul Rahman Sani, Abbas Z. Kouzani, Yijia Wu, Markus P. Nemitz, Masoud Shirzad, Dageon Oh, Seung Yun Nam, Amedeo Franco Bonatti, Irene Chiesa, Gabriele Maria Fortunato, Giovanni Vozzi, Carmelo De Maria, Mahdi Bodaghi   +37 more
wiley   +1 more source

Understanding the Lived Experience of Family Caregivers of Loved Ones in Long-Term Care During COVID-19 Through Art. [PDF]

Int J Environ Res Public Health
Christianson TM, Appiah-Kusi E, Bremner J.   +2 more
europepmc   +1 more source

Cryogenic Neuromorphic Synaptic Behavior in 180 nm Silicon Transistors for Emerging Computing Systems

Advanced Intelligent Systems, EarlyView.
This study investigates the neuromorphic plasticity behavior of 180 nm bulk complementary metal oxide semiconductor (CMOS) transistors at cryogenic temperatures. The observed hysteresis data reveal a signature of synaptic behavior in CMOS transistors at 4 K.
Fiheon Imroze, Bhavani Yalagala, Naveen Kumar, Mostafa Elsayed, Meraj Ahmad, Robert Graham, Vihar Georgiev, Hadi Heidari, Martin Weides   +8 more
wiley   +1 more source

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

Advanced 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, Md. Abdur Rahman, Mohaimenul Azam Khan Raiaan, Sami Azam   +3 more
wiley   +1 more source

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

Advanced 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, Norelli Schettini, Winston Percybrooks, Begoña García‐Zapirain   +3 more
wiley   +1 more source