Results 151 to 160 of about 118,357 (248)

AI‐Assisted IoT‐Enabled ECG Monitoring: Integrating Foundational and Generative AI Tools for Sustainable Smart Healthcare—Recent Trends

AI &Innovation, EarlyView.
ABSTRACT The rapid evolution of the Internet of Things (IoT) has significantly advanced the field of electrocardiogram (ECG) monitoring, enabling real‐time, remote, and patient‐centric cardiac care. This paper presents a comprehensive survey of AI assisted IoT‐based ECG monitoring systems, focusing on the integration of emerging technologies such as ...
Amrita Choudhury, Kandarpa Kumar Sarma, Lachit Dutta   +2 more
wiley   +1 more source

Domain‐adapted driving scene understanding with uncertainty‐aware and diversified generative adversarial networks

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Autonomous vehicles are required to operate in an uncertain environment. Recent advances in computational intelligence techniques make it possible to understand driving scenes in various environments by using a semantic segmentation neural network, which assigns a class label to each pixel.
Yining Hua, Jie Sui, Hui Fang, Chuan Hu, Dewei Yi   +4 more
wiley   +1 more source

Behavior Decoding Delineates Seizure Microfeatures and Associated Sudden Death Risks in Mouse Models of Epilepsy

Annals of Neurology, EarlyView.
Objective Behavior and motor manifestations are distinctive yet often overlooked features of epileptic seizures. Seizures can result in transient disruptions in motor control, often organized into specific behavioral sequences that can inform seizure types, onset zones, and outcomes.
Yuyan Shen, Jaden Thomas, Xianhui Chen, Jaden Zelidon, Mariam Najeeb, Abigayle Hahn, Ping Zhang, Aaron Sathyanesan, Bin Gu   +8 more
wiley   +1 more source

L-Lipschitz Gershgorin ResNet Network

Deep residual networks (ResNets) have demonstrated outstanding success in computer vision tasks, attributed to their ability to maintain gradient flow through deep architectures. Simultaneously, controlling the Lipschitz bound in neural networks has emerged as an essential area of research for enhancing adversarial robustness and network certifiability.
Juston, Marius F. R., Norris, William R., Nottage, Dustin, Soylemezoglu, Ahmet   +3 more
openaire   +2 more sources

Sustainable Live Sound Monitoring and Classification System Enabled by a Triboelectric Nanogenerator and Machine Learning Techniques

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
A high‐performance Triboelectric Nanogenerator (TENG) acoustic sensor using polyimine/graphite polypropylene (PI/GP) was developed for real‐time, sustainable sound monitoring and classification. The self‐powered device delivers 25.67 μW output power, 92.7% accuracy with MobileNet V1, and powers a wireless transmission circuit, demonstrating dual ...
Majid Haji Bagheri, Araz Rajabi‐Abhari, Owen Gibbs, Pengcheng Xi, Asif Abdullah Khan, Fangzheng Huang, Md Soyaeb Hassan, Ning Yan, Dayan Ban   +8 more
wiley   +1 more source

Real world testing and cost‐effectiveness analysis of subcutaneous EEG (REAL‐ASE): Protocol for a prospective multicentre interventional trial

Epilepsia Open, EarlyView.
Abstract Objective Epilepsy is a common condition associated with significant morbidity, mortality, and costs. Poor documentation of seizures is a major challenge in epilepsy care. Objective seizure counting with mobile devices may mitigate this challenge and improve patient management.
Matthew McWilliam, Pedro F. Viana, Eren Dursun, Joe Davies, Joel S. Winston, Jessica Agren, Harutomo Hasegawa, Jonas Duun‐Henriksen, Mark P. Richardson   +8 more
wiley   +1 more source

AI‐based localization of the epileptogenic zone using intracranial EEG

Epilepsia Open, EarlyView.
Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida, Yipeng Zhang, Sotaro Kanai, Richard Staba, Vwani Roychowdhury, Hiroki Nariai   +5 more
wiley   +1 more source

Harnessing deep learning to quantify microstructural complexity in confocal images of plant protein gels

Food Biomacromolecules, EarlyView.
Abstract Understanding plant protein gel microstructure is key to designing functional food systems. This study introduces a deep learning framework using a U‐Net model with a ResNet34 encoder to segment and quantify confocal laser scanning microscopy (CLSM) images of plant protein gels.
Zhi Yang
wiley   +1 more source

Facial expression recognition for emotion perception: A comprehensive science mapping

Ibrain, EarlyView.
Facial expression recognition (FER) has emerged as a pivotal interdisciplinary research domain, bridging computer science, psychology, neuroscience, and medicine. By mapping the FER scientific knowledge graph, the study aimed to explore the technological evolution and forecast future application trends in this field.
Hou‐Ming Kan, Li‐Ping Chen, Yu Zhang, Hao‐Yuan Hong, Ying‐Ying Qin, Yu‐Guo Cui, Yu‐Bo Mao, Yan‐Zhi Cheng, Zhe Lu, Hong‐Yan Ni, Xiao‐Tong Ding   +10 more
wiley   +1 more source

Artificial intelligence application in the prediction of spontaneous preterm birth by cervical length in the first trimester of pregnancy: Comparison of three measurement methods

International Journal of Gynecology &Obstetrics, EarlyView.
Abstract Objectives The current study evaluates the efficacy of artificial intelligence (AI)–assisted measurement of cervical length (CL) in predicting spontaneous preterm birth (sPTB), comparing the traditional single‐line and two‐line methods with the innovative AI‐line method in the first trimester of pregnancy. Materials and Methods This study is a
Yi‐yun Tai, Bor‐Yann Tseng, Zhu‐Han Yang, Chi‐Hua Yu, Liona C. Poon   +4 more
wiley   +1 more source