Results 61 to 70 of about 6,341 (246)

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

Artificial intelligence in enzyme catalysis: Emerging trends and applications in biocatalyst engineering

The Canadian Journal of Chemical Engineering, EarlyView.
Schematic representation of artificial intelligence approaches in enzyme catalysis, integrating bibliometric analysis, emerging research trends, and machine learning tools for enzyme design, prediction, and industrial biocatalytic applications. Abstract This study systematically explores the applications of artificial intelligence (AI) in enzyme ...
Misael Bessa Sales, Francisco Izaias da Silva Aires, Paulo Gonçalves de Sousa Junior, Calebe Da Rocha Silva, Emanuel Lino Rodrigues, Maria Cristiane Martins de Souza, José C. S. dos Santos   +6 more
wiley   +1 more source

A Two-Stage Generative Adversarial Networks With Semantic Content Constraints for Adversarial Example Generation

IEEE Access, 2020
Deep neural networks (DNNs) have achieved great success in various applications due to their strong expressive power. However, recent studies have shown that DNNs are vulnerable to adversarial examples, and these manipulated instances can mislead DNN ...
Jianyi Liu, Yu Tian, Ru Zhang, Youqiang Sun, Chan Wang   +4 more
doaj   +1 more source

A Distributed Biased Boundary Attack Method in Black-Box Attack

Applied Sciences, 2021
The adversarial samples threaten the effectiveness of machine learning (ML) models and algorithms in many applications. In particular, black-box attack methods are quite close to actual scenarios.
Fengtao Xiang, Jiahui Xu, Wanpeng Zhang, Weidong Wang   +3 more
doaj   +1 more source

From Executor to Orchestrator: The Pharmacology Scientist in the Age of Agentic AI

Clinical Pharmacology &Therapeutics, EarlyView.
Drug development productivity has not improved despite five decades of computational advancement, with the probability that a compound entering Phase I achieving regulatory approval remaining near 10%. Each automation wave increased throughput while leaving the interpretive bottleneck intact; scientists continued to formulate questions, evaluate ...
Michael McCoy, Matthew McCoy
wiley   +1 more source

Link Prediction Adversarial Attack

CoRR, 2018
Deep neural network has shown remarkable performance in solving computer vision and some graph evolved tasks, such as node classification and link prediction. However, the vulnerability of deep model has also been revealed by carefully designed adversarial examples generated by various adversarial attack methods.
Jinyin Chen, Ziqiang Shi, Yangyang Wu, Xuanheng Xu, Haibin Zheng   +4 more
openaire   +2 more sources

A Review of Artificial Intelligence in Ophthalmology: Key Aspects, Challenges, and Future Directions

Eye &ENT Research, EarlyView.
ABSTRACT Artificial intelligence (AI) is increasingly reshaping ophthalmology because the specialty depends heavily on structured imaging, quantitative measurements, and repeatable diagnostic workflows. This review provides a clinically grounded and translationally oriented synthesis of AI in ophthalmology, covering methodological foundations ...
Partha Pratim Ray
wiley   +1 more source

Enhancing Adversarial Attacks via Parameter Adaptive Adversarial Attack

CoRR
In recent times, the swift evolution of adversarial attacks has captured widespread attention, particularly concerning their transferability and other performance attributes. These techniques are primarily executed at the sample level, frequently overlooking the intrinsic parameters of models.
Zhibo Jin, Jiayu Zhang 0001, Zhiyu Zhu, Chenyu Zhang, Jiahao Huang, Jianlong Zhou, Fang Chen 0001   +6 more
openaire   +2 more sources

Artificial intelligence for adaptive neuromodulation in drug‐resistant epilepsy

Epilepsia, EarlyView.
Abstract Drug‐resistant epilepsy (DRE) affects nearly one third of people with epilepsy and is associated with substantial cognitive, psychiatric, and mortality burdens. For patients who are not candidates for resection or laser interstitial thermal therapy, neuromodulation therapies such as vagus nerve stimulation, deep brain stimulation, and ...
Amir Hossein Daraie, Arianna Damiani, Mahsa Khoshkhou, Luis A. Sanchez, Rachel J. Smith, Shruti H. Agashe, Jorge A. Gonzalez‐Martinez, Jennifer Hopp, Adam S. Charles, Sridevi V. Sarma, Joon‐Yi Kang   +10 more
wiley   +1 more source

Multi-Level Chinese Adversarial Example Generation Method Based on Glyph and Semantic [PDF]

Jisuanji gongcheng
Deep neural network language models are vulnerable to adversarial example attacks during application. To address this issue, adversarial examples are typically generated by adding minor perturbations to the original samples to mislead the model into ...
SUN Yu, WANG Hongjie, DU Yanhui, LIU Nan
doaj   +1 more source