Deep learning and artificial intelligence in action (2019-2023): A review on brain stroke detection, diagnosis, and intelligent post-stroke rehabilitation management
J Chaki, M Woźniak - IEEE Access, 2024 - ieeexplore.ieee.org
Brain stroke is a complicated disease that is one of the foremost reasons of long-term
debility and mortality. Because of breakthroughs in Deep Learning (DL) and Artificial …
debility and mortality. Because of breakthroughs in Deep Learning (DL) and Artificial …
Lite-FBCN: Lightweight Fast Bilinear Convolutional Network for Brain Disease Classification from MRI Image
DJ Rumala, RF Rachmadi, AD Sensusiati… - arXiv preprint arXiv …, 2024 - arxiv.org
Achieving high accuracy with computational efficiency in brain disease classification from
Magnetic Resonance Imaging (MRI) scans is challenging, particularly when both coarse and …
Magnetic Resonance Imaging (MRI) scans is challenging, particularly when both coarse and …
Triple Diseases Prediction System using Deep Learning Techniques
R Vijayan, V Mareeswari… - … Conference on Emerging …, 2024 - ieeexplore.ieee.org
With the existing deep learning models in predicting multiple diseases primarily focus on
analyzing individual diseases in isolation, lacking a unified system for multi-disease …
analyzing individual diseases in isolation, lacking a unified system for multi-disease …
A Digital Twin-based Method for Identifying Weak Points in Integrated Energy Smart Systems
Y Yuan, Y Li - 2024 6th International Conference on Energy …, 2024 - ieeexplore.ieee.org
The setting of weak point identification nodes in integrated energy intelligent systems is
usually based on basic layout, with a low identification frequency, resulting in an increase in …
usually based on basic layout, with a low identification frequency, resulting in an increase in …