Results 101 to 110 of about 96,144 (271)

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

Challenges and Countermeasures of Federated Learning Data Poisoning Attack Situation Prediction

Mathematics
Federated learning is a distributed learning method used to solve data silos and privacy protection in machine learning, aiming to train global models together via multiple clients without sharing data.
Jianping Wu, Jiahe Jin, Chunming Wu
doaj   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

Federated Learning in Data Privacy and Security

Advances in Distributed Computing and Artificial Intelligence Journal
Federated learning (FL) has been a rapidly growing topic in recent years. The biggest concern in federated learning is data privacy and cybersecurity. There are many algorithms that federated models have to work on to achieve greater efficiency, security,
Dokuru Trisha Reddy, Haripriya Nandigam, Sai Charan Indla, S. P. Raja   +3 more
doaj   +1 more source

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

Federated Versus Central Machine Learning on Diabetic Foot Ulcer Images: Comparative Simulations

IEEE Access
This research examines the implementation of the U-Net model within a federated learning framework, focusing on the semantic segmentation of Diabetic Foot Ulcers (DFUs) images.
Mahdi Saeedi, Hamed Taheri Gorji, Fartash Vasefi, Kouhyar Tavakolian   +3 more
doaj   +1 more source

Toward Quantum Federated Learning

IEEE Transactions on Neural Networks and Learning Systems
Quantum Federated Learning (QFL) is an emerging interdisciplinary field that merges the principles of Quantum Computing (QC) and Federated Learning (FL), with the goal of leveraging quantum technologies to enhance privacy, security, and efficiency in the learning process.
Chao Ren, Rudai Yan, Huihui Zhu, Han Yu, Minrui Xu, Yuan Shen, Yan Xu, Ming Xiao, Zhao Yang Dong, Mikael Skoglund, Dusit Niyato, Leong Chuan Kwek   +11 more
openaire   +3 more sources

Confessions of a Poverty Researcher: My Journey Through the Foothills of Scholarship

Australian Journal of Social Issues, EarlyView.
ABSTRACT This paper describes the key events, experiences and ideas that influenced the author's career as a poverty researcher. He describes how his early disillusion with economics was replaced by a spark of interest in social issues and how his migration from the UK to Australia in the mid‐1970s provided the impetus to begin what became a lifetime ...
Peter Saunders
wiley   +1 more source

Survey on incentive-driven federated learning: privacy and security

网络与信息安全学报
Federated learning was enabled to allow multiple data holders to jointly complete machine learning tasks without disclosing local data. Incentivizing participants to engage in federated learning and contribute high-quality data was identified as one of ...
CHI Huanhuan, XIONG Ping, LIU Hengzhu, MA Xiao, ZHU Tianqing   +4 more
doaj  

The Politics of Framing the Student Problem: Inquiries Into Australian Civics Education, 2006–2024

Australian Journal of Social Issues, EarlyView.
ABSTRACT Recurring debates about civics, the kinds of history that should, and should not, be taught in school, and ‘standards debates’ about the ‘basics’ typically follow on the heels of recurring moral panics about the ‘declining’ state of ‘our’ education system.
Patrick O'Keeffe, Judith Bessant, Madeline Drake   +2 more
wiley   +1 more source