Brain Informatics
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Interpreting artificial intelligence models: a systematic review on the application of LIME and SHAP in Alzheimer’s disease detection
Brain Informatics - - 2024
Explainable artificial intelligence (XAI) has gained much interest in recent years for its ability to explain the complex decision-making process of machine learning (ML) and deep learning (DL) models. The Local Interpretable Model-agnostic Explanations (LIME) and Shaply Additive exPlanation (SHAP) frameworks have grown as popular interpretive tools for ML and DL models. This article provides a sy......
A multi-expert ensemble system for predicting Alzheimer transition using clinical features
Brain Informatics - Tập 9 - Trang 1-11 - 2022
Alzheimer’s disease (AD) diagnosis often requires invasive examinations (e.g., liquor analyses), expensive tools (e.g., brain imaging) and highly specialized personnel. The diagnosis commonly is established when the disorder has already caused severe brain damage, and the clinical signs begin to be apparent. Instead, accessible and low-cost approaches for early identification of subjects at high r......
3D convolutional neural networks uncover modality-specific brain-imaging predictors for Alzheimer’s disease sub-scores
Brain Informatics - Tập 11 - Trang 1-11 - 2024
Different aspects of cognitive functions are affected in patients with Alzheimer’s disease. To date, little is known about the associations between features from brain-imaging and individual Alzheimer’s disease (AD)-related cognitive functional changes. In addition, how these associations differ among different imaging modalities is unclear. Here, we trained and investigated 3D convolutional neura......
An adaptive annotation approach for biomedical entity and relation recognition
Brain Informatics - Tập 3 - Trang 157-168 - 2016
In this article, we demonstrate the impact of interactive machine learning: we develop biomedical entity recognition dataset using a human-into-the-loop approach. In contrary to classical machine learning, human-in-the-loop approaches do not operate on predefined training or test sets, but assume that human input regarding system improvement is supplied iteratively. Here, during annotation, a mac......
Local dimension-reduced dynamical spatio-temporal models for resting state network estimation
Brain Informatics - Tập 2 - Trang 53-63 - 2015
To overcome the limitations of independent component analysis (ICA), today’s most popular analysis tool for investigating whole-brain spatial activation in resting state functional magnetic resonance imaging (fMRI), we present a new class of local dimension-reduced dynamical spatio-temporal model which dispenses the independence assumptions that severely limit deeper connectivity descriptions betw......
Machine learning determination of applied behavioral analysis treatment plan type
Brain Informatics - Tập 10 - Trang 1-19 - 2023
Applied behavioral analysis (ABA) is regarded as the gold standard treatment for autism spectrum disorder (ASD) and has the potential to improve outcomes for patients with ASD. It can be delivered at different intensities, which are classified as comprehensive or focused treatment approaches. Comprehensive ABA targets multiple developmental domains and involves 20–40 h/week of treatment. Focused A......
Near-channel classifier: symbiotic communication and classification in high-dimensional space
Brain Informatics - Tập 8 - Trang 1-15 - 2021
Brain-inspired high-dimensional (HD) computing represents and manipulates data using very long, random vectors with dimensionality in the thousands. This representation provides great robustness for various classification tasks where classifiers operate at low signal-to-noise ratio (SNR) conditions. Similarly, hyperdimensional modulation (HDM) leverages the robustness of complex-valued HD represen......
EEG-based human emotion recognition using entropy as a feature extraction measure
Brain Informatics - Tập 8 - Trang 1-13 - 2021
Many studies on brain–computer interface (BCI) have sought to understand the emotional state of the user to provide a reliable link between humans and machines. Advanced neuroimaging methods like electroencephalography (EEG) have enabled us to replicate and understand a wide range of human emotions more precisely. This physiological signal, i.e., EEG-based method is in stark comparison to traditio......
Common spatial pattern for classification of loving kindness meditation EEG for single and multiple sessions
Brain Informatics - Tập 10 - Trang 1-15 - 2023
While a very few studies have been conducted on classifying loving kindness meditation (LKM) and non-meditation electroencephalography (EEG) data for a single session, there are no such studies conducted for multiple session EEG data. Thus, this study aims at classifying existing raw EEG meditation data on single and multiple sessions to come up with meaningful inferences which will be highly bene......
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