4.7 Article

Multimodal Triplet Attention Network for Brain Disease Diagnosis

Related references

Note: Only part of the references are listed.
Article Psychiatry

Mapping relationships among schizophrenia, bipolar and schizoaffective disorders: A deep classification and clustering framework using fMRI time series

Weizheng Yan et al.

Summary: This study proposes a framework for the classification and clustering of psychiatric disorders using brain imaging data. They developed a new multi-scale recurrent neural network model and successfully achieved multi-class classification of mental illnesses, visualizing the differences between different disorders. They also identified biomarkers related to the classification.

SCHIZOPHRENIA RESEARCH (2022)

Article Computer Science, Artificial Intelligence

MetaCOVID: A Siamese neural network framework with contrastive loss for n -shot diagnosis of COVID-19 patients

Mohammad Shorfuzzaman et al.

Summary: An AI system based on deep meta learning was proposed to accelerate analysis of chest X-ray (CXR) images for automatic detection of COVID-19 cases. The model integrates contrastive learning and a fine-tuned pre-trained ConvNet encoder to capture unbiased feature representations, achieving 95.6% accuracy and AUC of 0.97 in diagnosing COVID-19 from CXR images.

PATTERN RECOGNITION (2021)

Article Neurosciences

Deep sr-DDL: Deep structurally regularized dynamic dictionary learning to integrate multimodal and dynamic functional connectomics data for multidimensional clinical characterizations

N. S. D'Souza et al.

Summary: The framework combines rs-fMRI connectivity and DTI tractography data to extract biomarkers predictive of behavior, using a generative model of connectomics data and a deep network to predict behavioral scores. Joint optimization strategy estimates basis networks, subject-specific loadings, and neural network weights. The hybrid model outperforms state-of-the-art approaches in clinical outcome prediction and learns interpretable multimodal neural signatures of brain organization.

NEUROIMAGE (2021)

Article Multidisciplinary Sciences

MedFuseNet: An attention-based multimodal deep learning model for visual question answering in the medical domain

Dhruv Sharma et al.

Summary: Medical images are complex for non-experts, and healthcare professionals can face fatigue and errors due to high case loads. Therefore, developing a reliable VQA system specific to medical images is crucial for enhancing confidence among decision makers.

SCIENTIFIC REPORTS (2021)

Article Robotics

Multi-GAT: A Graphical Attention-Based Hierarchical Multimodal Representation Learning Approach for Human Activity Recognition

Md Mofijul Islam et al.

Summary: This study presents a multimodal graphical attention-based human activity recognition approach, Multi-GAT, which hierarchically learns complementary multimodal features and outperforms other HAR algorithms, especially in noisy environments.

IEEE ROBOTICS AND AUTOMATION LETTERS (2021)

Article Computer Science, Information Systems

An Attention-Based Mechanism to Combine Images and Metadata in Deep Learning Models Applied to Skin Cancer Classification

Andre G. C. Pacheco et al.

Summary: This article explores the combination of images and metadata features in deep learning models for skin cancer classification, introducing the MetaBlock algorithm for enhancing classification with metadata. Results demonstrate that considering metadata can improve classification performance, outperforming other combination approaches in certain scenarios.

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2021)

Article Engineering, Electrical & Electronic

Few-Shot Learning for Palmprint Recognition via Meta-Siamese Network

Huikai Shao et al.

Summary: The article introduces a novel meta-Siamese network for small-sample palmprint recognition, which learns feature embedding and deep similarity metric function through episodic training and introduces two distance-based losses for optimization. Experimental results show that the method has competitive advantages in palmprint recognition, with the highest accuracy reaching 100%.

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2021)

Proceedings Paper Computer Science, Artificial Intelligence

Medical Transformer: Gated Axial-Attention for Medical Image Segmentation

Jeya Maria Jose Valanarasu et al.

Summary: Deep convolutional neural networks have been widely adopted in medical image segmentation, but lack understanding of long-range dependencies due to inherent biases in convolutional architectures. Transformer-based architectures leverage self-attention mechanism to encode long-range dependencies, motivating the exploration of transformer solutions for medical image segmentation tasks.

MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2021, PT I (2021)

Review Public, Environmental & Occupational Health

The Epidemiology of Epilepsy

Ettore Beghi

NEUROEPIDEMIOLOGY (2020)

Article Computer Science, Interdisciplinary Applications

Self-Supervised Feature Learning via Exploiting Multi-Modal Data for Retinal Disease Diagnosis

Xiaomeng Li et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2020)

Article Computer Science, Artificial Intelligence

Multimodal Machine Learning: A Survey and Taxonomy

Tadas Baltrusaitis et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2019)

Article Biotechnology & Applied Microbiology

Attention-Based Multi-NMF Deep Neural Network with Multimodality Data for Breast Cancer Prognosis Model

Hongling Chen et al.

BIOMED RESEARCH INTERNATIONAL (2019)

Article Multidisciplinary Sciences

Decoupling of brain function from structure reveals regional behavioral specialization in humans

Maria Giulia Preti et al.

NATURE COMMUNICATIONS (2019)

Article Computer Science, Information Systems

Few-shot learning for short text classification

Leiming Yan et al.

MULTIMEDIA TOOLS AND APPLICATIONS (2018)

Review Psychology, Multidisciplinary

What We Know About the Brain Structure-Function Relationship

Karla Batista-Garcia-Ramo et al.

BEHAVIORAL SCIENCES (2018)

Article Multidisciplinary Sciences

Overcoming catastrophic forgetting in neural networks

James Kirkpatricka et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2017)

Proceedings Paper Computer Science, Artificial Intelligence

Attention-Based Multimodal Fusion for Video Description

Chiori Hori et al.

2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) (2017)

Review Clinical Neurology

Epilepsy surgery in children and adults

Philippe Ryvlin et al.

LANCET NEUROLOGY (2014)

Article Clinical Neurology

Frontal lobe connectivity and cognitive impairment in pediatric frontal lobe epilepsy

Hilde M. H. Braakman et al.

EPILEPSIA (2013)

Article Neurosciences

PANDA: a pipeline toolbox for analyzing brain diffusion images

Zaixu Cui et al.

FRONTIERS IN HUMAN NEUROSCIENCE (2013)

Review Behavioral Sciences

Epilepsy and the frontal lobes

Jonathan O'Muircheartaigh et al.

CORTEX (2012)

Article Clinical Neurology

Patterns of altered functional connectivity in mesial temporal lobe epilepsy

Francesca Pittau et al.

EPILEPSIA (2012)

Article Multidisciplinary Sciences

White matter maturation reshapes structural connectivity in the late developing human brain

P. Hagmann et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2010)

Article Neurosciences

DPARSF: a MATLAB toolbox for pipeline data analysis of resting- state fMRI

Yan Chao-Gan et al.

FRONTIERS IN SYSTEMS NEUROSCIENCE (2010)

Article Computer Science, Artificial Intelligence

MPCA: Multilinear principal component analysis of tensor objects

Haiping Lu et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS (2008)