Advances in AI and machine learning for predictive medicine
The field of omics, driven by advances in high-throughput sequencing, faces a data
explosion. This abundance of data offers unprecedented opportunities for predictive …
explosion. This abundance of data offers unprecedented opportunities for predictive …
DeepInsight-3D architecture for anti-cancer drug response prediction with deep-learning on multi-omics
Modern oncology offers a wide range of treatments and therefore choosing the best option
for particular patient is very important for optimal outcome. Multi-omics profiling in …
for particular patient is very important for optimal outcome. Multi-omics profiling in …
Explainable artificial intelligence approaches for brain-computer interfaces: a review and design space
This review paper provides an integrated perspective of Explainable Artificial Intelligence
techniques applied to Brain-Computer Interfaces. BCIs use predictive models to interpret …
techniques applied to Brain-Computer Interfaces. BCIs use predictive models to interpret …
A new algorithm and damage index for detection damage in steel girders of bridge decks using time-frequency domain and matching methods
HR Ahmadi, K Momeni, Y Jasemnejad - Structures, 2024 - Elsevier
Damage identification, especially in the early stages, is one of the most important factors in
preserving and maintaining structures and infrastructures. Structural Damage can lead to …
preserving and maintaining structures and infrastructures. Structural Damage can lead to …
An efficient deep learning framework for P300 evoked related potential detection in EEG signal
Background Incorporating the time-frequency localization properties of Gabor transform
(GT), the complexity understandings of convolutional neural network (CNN), and histogram …
(GT), the complexity understandings of convolutional neural network (CNN), and histogram …
Enhanced analysis of tabular data through Multi-representation DeepInsight
Tabular data analysis is a critical task in various domains, enabling us to uncover valuable
insights from structured datasets. While traditional machine learning methods can be used …
insights from structured datasets. While traditional machine learning methods can be used …
A novel multiclass-based framework for P300 detection in BCI matrix speller: Temporal EEG patterns of non-target trials vary based on their position to previous target …
Brain–computer interface (BCI) provides a new communication pathway for severely
disabled people and enables them to communicate with external world using only their brain …
disabled people and enables them to communicate with external world using only their brain …
Dynamical Differential Covariance based Brain Network for Motor Intent Recognition
R Fu, Y Du, S Wang, G Wen, J Chen… - IEEE Sensors Journal, 2024 - ieeexplore.ieee.org
In the field of motor imagery (MI) recognition based on electroencephalogram (EEG),
complex network-based analysis of brain connectivity has gained significant attention …
complex network-based analysis of brain connectivity has gained significant attention …
A Temporal-Spectral Fusion Transformer with Subject-specific Adapter for Enhancing RSVP-BCI Decoding
X Li, W Wei, S Qiu, H He - arXiv preprint arXiv:2401.06340, 2024 - arxiv.org
The Rapid Serial Visual Presentation (RSVP)-based Brain-Computer Interface (BCI) is an
efficient technology for target retrieval using electroencephalography (EEG) signals. The …
efficient technology for target retrieval using electroencephalography (EEG) signals. The …
Multi-representation DeepInsight: an improvement on tabular data analysis
Tabular data analysis is a critical task in various domains, enabling us to uncover valuable
insights from structured datasets. While traditional machine learning methods have been …
insights from structured datasets. While traditional machine learning methods have been …