[HTML][HTML] Explainable artificial intelligence (XAI) in deep learning-based medical image analysis
With an increase in deep learning-based methods, the call for explainability of such methods
grows, especially in high-stakes decision making areas such as medical image analysis …
grows, especially in high-stakes decision making areas such as medical image analysis …
Braingnn: Interpretable brain graph neural network for fmri analysis
Understanding which brain regions are related to a specific neurological disorder or
cognitive stimuli has been an important area of neuroimaging research. We propose …
cognitive stimuli has been an important area of neuroimaging research. We propose …
Interpreting mental state decoding with deep learning models
In mental state decoding, researchers aim to identify the set of mental states (eg,
experiencing happiness or fear) that can be reliably identified from the activity patterns of a …
experiencing happiness or fear) that can be reliably identified from the activity patterns of a …
Pooling regularized graph neural network for fmri biomarker analysis
Understanding how certain brain regions relate to a specific neurological disorder has been
an important area of neuroimaging research. A promising approach to identify the salient …
an important area of neuroimaging research. A promising approach to identify the salient …
Self-supervised learning of brain dynamics from broad neuroimaging data
Self-supervised learning techniques are celebrating immense success in natural language
processing (NLP) by enabling models to learn from broad language data at unprecedented …
processing (NLP) by enabling models to learn from broad language data at unprecedented …
[HTML][HTML] Brain structure-function coupling provides signatures for task decoding and individual fingerprinting
Brain signatures of functional activity have shown promising results in both decoding brain
states, meaning distinguishing between different tasks, and fingerprinting, that is identifying …
states, meaning distinguishing between different tasks, and fingerprinting, that is identifying …
[HTML][HTML] Functional annotation of human cognitive states using deep graph convolution
A key goal in neuroscience is to understand brain mechanisms of cognitive functions. An
emerging approach is “brain decoding”, which consists of inferring a set of experimental …
emerging approach is “brain decoding”, which consists of inferring a set of experimental …
Deep learning object detection of maxillary cyst-like lesions on panoramic radiographs: preliminary study
H Watanabe, Y Ariji, M Fukuda, C Kuwada, Y Kise… - Oral radiology, 2021 - Springer
Objectives This study aimed to examine the performance of deep learning object detection
technology for detecting and identifying maxillary cyst-like lesions on panoramic …
technology for detecting and identifying maxillary cyst-like lesions on panoramic …
Recent advances in explainable artificial intelligence for magnetic resonance imaging
Advances in artificial intelligence (AI), especially deep learning (DL), have facilitated
magnetic resonance imaging (MRI) data analysis, enabling AI-assisted medical image …
magnetic resonance imaging (MRI) data analysis, enabling AI-assisted medical image …
Alzheimer's Disease Detection Using Deep Learning on Neuroimaging: A Systematic Review
Alzheimer's disease (AD) is a pressing global issue, demanding effective diagnostic
approaches. This systematic review surveys the recent literature (2018 onwards) to …
approaches. This systematic review surveys the recent literature (2018 onwards) to …