[PDF][PDF] Enhancing Healthcare Data Security and Disease Detection Using Crossover-Based Multilayer Perceptron in Smart Healthcare Systems.
MH Abidi, H Alkhalefah… - CMES-Computer Modeling …, 2024 - researchgate.net
The healthcare data requires accurate disease detection analysis, real-time monitoring, and
advancements to ensure proper treatment for patients. Consequently, Machine Learning …
advancements to ensure proper treatment for patients. Consequently, Machine Learning …
Adversarial attacks to machine learning-based smart healthcare systems
AKM Iqtidar Newaz, N Imtiazul Haque… - arXiv e …, 2020 - ui.adsabs.harvard.edu
The increasing availability of healthcare data requires accurate analysis of disease
diagnosis, progression, and realtime monitoring to provide improved treatments to the …
diagnosis, progression, and realtime monitoring to provide improved treatments to the …
Adversarial attacks to machine learning-based smart healthcare systems
The increasing availability of healthcare data requires accurate analysis of disease
diagnosis, progression, and real-time monitoring to provide improved treatments to the …
diagnosis, progression, and real-time monitoring to provide improved treatments to the …
Machine learning vulnerability in medical imaging
TV Maliamanis, GA Papakostas - Machine Learning, Big Data, and IoT for …, 2021 - Elsevier
Recently, there has been increased interest in applying computer vision methodologies in
medical imaging, mainly due to the outstanding performance of deep learning. However …
medical imaging, mainly due to the outstanding performance of deep learning. However …
Addressing adversarial machine learning attacks in smart healthcare perspectives
A Selvakkumar, S Pal, Z Jadidi - Sensing Technology: Proceedings of ICST …, 2022 - Springer
Smart healthcare systems are gaining popularity with the rapid development of intelligent
sensors, the Internet of Things (IoT) applications and services, and wireless …
sensors, the Internet of Things (IoT) applications and services, and wireless …
Malware Attacks on Electronic Health Records
SG Selvaganapathy, S Sadasivam - … : Proceedings of CIS 2020, Volume 1, 2021 - Springer
Technological advancements along with the surge of high-speed Internet has enabled
healthcare organizations (HCO) to provide enhanced medical treatment and better patient …
healthcare organizations (HCO) to provide enhanced medical treatment and better patient …
[HTML][HTML] Detection of Adversarial Attacks against the Hybrid Convolutional Long Short-Term Memory Deep Learning Technique for Healthcare Monitoring Applications
A Albattah, MA Rassam - Applied Sciences, 2023 - mdpi.com
Deep learning (DL) models are frequently employed to extract valuable features from
heterogeneous and high-dimensional healthcare data, which are used to keep track of …
heterogeneous and high-dimensional healthcare data, which are used to keep track of …
[HTML][HTML] Mitigating adversarial evasion attacks by deep active learning for medical image classification
U Ahmed, JCW Lin, G Srivastava - Multimedia Tools and Applications, 2022 - Springer
Abstract In the Internet of Medical Things (IoMT), collaboration among institutes can help
complex medical and clinical analysis of disease. Deep neural networks (DNN) require …
complex medical and clinical analysis of disease. Deep neural networks (DNN) require …
The Impact of Simultaneous Adversarial Attacks on Robustness of Medical Image Analysis
Deep learning models are widely used in healthcare systems. However, deep learning
models are vulnerable to attacks themselves. Significantly, due to the black-box nature of the …
models are vulnerable to attacks themselves. Significantly, due to the black-box nature of the …
Privacy-aware early detection of COVID-19 through adversarial training
Early detection of COVID-19 is an ongoing area of research that can help with triage,
monitoring and general health assessment of potential patients and may reduce operational …
monitoring and general health assessment of potential patients and may reduce operational …