Results 41 to 50 of about 6,980 (145)

Artificial Intelligence in Ophthalmology: From Methodological Advances to Clinical Translation and Future Directions

Eye &ENT Research, EarlyView.
ABSTRACT Artificial intelligence (AI) is reshaping ophthalmology from task‐specific image analysis toward multimodal, longitudinal, and clinically integrated decision support. This narrative review summarizes the methodological evolution of ophthalmic AI, including traditional machine learning, task‐specific deep learning, self‐supervised learning ...
Yuxin Liu, Hanruo Liu
wiley   +1 more source

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

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

Deep Reinforcement Learning-Based Adversarial Attack and Defense in Industrial Control Systems

Mathematics
Adversarial attacks targeting industrial control systems, such as the Maroochy wastewater system attack and the Stuxnet worm attack, have caused significant damage to related facilities.
Mun-Suk Kim
doaj   +1 more source

Review of Research on Adversarial Attack in Three Kinds of Images [PDF]

Jisuanji kexue yu tansuo
In recent years, there have been numerous breakthroughs in deep learning, leading to the expansion of applications based on deep learning into a wide range of fields.
XU Yuhui, PAN Zhisong, XU Kun
doaj   +1 more source

Predicting Solar Photovoltaic Power Output in Saudi Arabia's Jazan Region: Performance Comparison of Machine Learning Models

Energy Science &Engineering, EarlyView.
Workflow of the PV power estimation and ML forecasting methodology. ABSTRACT Accurate prediction of solar panel energy output is vital for managing power systems effectively and maintaining a stable electrical grid. This is especially important in regions that rely heavily on renewable sources. This research provides a direct comparison of five machine
Abdoalateef Alzhrani, Abdullahi Abubakar Mas'ud, Mohd Khairul Amri Kamarudin, Firdaus Muhammad‐Sukki, Abdullahi Mohammad   +4 more
wiley   +1 more source

Causality adversarial attack generation algorithm for intelligent unmanned communication system

Tongxin xuebao
A causality adversarial attack generation algorithm was proposed in response to the causality issue of gradient-based adversarial attack generation algorithms in practical communication system.The sequential input-output features and temporal memory ...
Shuwen YU, Wei XU, Jiacheng YAO
doaj   +2 more sources

Benign-salient Region Based End-to-End Adversarial Malware Generation Method [PDF]

Jisuanji kexue
Malware detection methods combining visualization techniques and deep learning have gained widespread attention due to their high accuracy and low cost.However,deep learning models are vulnerable to adversarial attacks,where intentional small-scale ...
YUAN Mengjiao, LU Tianliang, HUANG Wanxin, HE Houhan
doaj   +1 more source

From Physiology to Bioheat Simulation: A Data‐Driven Framework for Core Temperature Initialization

Heat Transfer, EarlyView.
ABSTRACT Accurate initialization of core body temperature is a critical yet often overlooked component of bioheat transfer models, particularly when such models are applied to heterogeneous populations and real‐world environmental conditions. Conventional bioheat simulations typically rely on fixed or idealized core body temperature values derived from
David S. Rodríguez, Ana S. Acosta, Carol D. Vergara, Daniela Martínez, Sebastián Bermúdez, Cristian F. Rodríguez, Juan C. Cruz   +6 more
wiley   +1 more source

An adversarial attack method based on pixel location characteristics

Journal of Intelligent Systems
Deep learning techniques have been widely used in various fields. However, they face significant security challenges due to the existence of adversarial examples.
Zhao Qin, Liu Jiuhong, Ma Xian, Liu Tongbo, Du Yingzhen   +4 more
doaj   +1 more source