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Found 13 papers, 9 papers with code
Multimodal Neurodegenerative Disease Subtyping Explained by ChatGPT
Thus, we propose a multimodal framework that uses early-stage indicators such as imaging, genetics and clinical assessments to classify AD patients into subtypes at early stages.
Spectral Adversarial MixUp for Few-Shot Unsupervised Domain Adaptation
To accomplish this challenging task, first, a spectral sensitivity map is introduced to characterize the generalization weaknesses of models in the frequency domain.
When Neural Networks Fail to Generalize? A Model Sensitivity Perspective
Domain generalization (DG) aims to train a model to perform well in unseen domains under different distributions.
Regression Metric Loss: Learning a Semantic Representation Space for Medical Images
Regression plays an essential role in many medical imaging applications for estimating various clinical risk or measurement scores.
Cross-modal Attention for MRI and Ultrasound Volume Registration
In the past few years, convolutional neural networks (CNNs) have been proved powerful in extracting image features crucial for image registration.
AnaXNet: Anatomy Aware Multi-label Finding Classification in Chest X-ray
Radiologists usually observe anatomical regions of chest X-ray images as well as the overall image before making a decision.
Task-Oriented Low-Dose CT Image Denoising
The extensive use of medical CT has raised a public concern over the radiation dose to the patient.
GaitSet: Cross-view Gait Recognition through Utilizing Gait as a Deep Set
In this paper, we present a novel perspective that utilizes gait as a deep set, which means that a set of gait frames are integrated by a global-local fused deep network inspired by the way our left- and right-hemisphere processes information to learn information that can be used in identification.
Robustified Domain Adaptation
Unsupervised domain adaptation (UDA) is widely used to transfer knowledge from a labeled source domain to an unlabeled target domain with different data distribution.
Deep Learning Predicts Cardiovascular Disease Risks from Lung Cancer Screening Low Dose Computed Tomography
Cancer patients have a higher risk of cardiovascular disease (CVD) mortality than the general population.
Integrative Analysis for COVID-19 Patient Outcome Prediction
Management of high-risk patients with early intervention is a key to lower the fatality rate of COVID-19 pneumonia, as a majority of patients recover naturally.
Towards a Precipitation Bias Corrector against Noise and Maldistribution
To the best of our knowledge, it is the first expert-free models for bias correction.
GaitSet: Regarding Gait as a Set for Cross-View Gait Recognition
In this paper we present a novel perspective, where a gait is regarded as a set consisting of independent frames.
Ranked #2 on
Multiview Gait Recognition
on OU-MVLP
