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Found 7 papers, 2 papers with code
Utilizing Large Language Models to Identify Reddit Users Considering Vaping Cessation for Digital Interventions
The widespread adoption of social media platforms globally not only enhances users' connectivity and communication but also emerges as a vital channel for the dissemination of health-related information, thereby establishing social media data as an invaluable organic data resource for public health research.
Flexible Variational Information Bottleneck: Achieving Diverse Compression with a Single Training
We theoretically demonstrate that across all values of reasonable $\beta$, FVIB can simultaneously maximize an approximation of the objective function for Variational Information Bottleneck (VIB), the conventional IB method.
Detecting Reddit Users with Depression Using a Hybrid Neural Network SBERT-CNN
In this work, we propose a hybrid deep learning model which combines a pretrained sentence BERT (SBERT) and convolutional neural network (CNN) to detect individuals with depression with their Reddit posts.
A New Outlier Removal Strategy Based on Reliability of Correspondence Graph for Fast Point Cloud Registration
We use a simple and intuitive method to describe the 6-DOF (degree of freedom) curtailment process in point cloud registration and propose an outlier removal strategy based on the reliability of the correspondence graph.
Automated Sleep Staging via Parallel Frequency-Cut Attention
This paper proposes a novel framework for automatically capturing the time-frequency nature of electroencephalogram (EEG) signals of human sleep based on the authoritative sleep medicine guidance.
Cancer Subtyping via Embedded Unsupervised Learning on Transcriptomics Data
In this paper, we propose to investigate automatic subtyping from an unsupervised learning perspective by directly constructing the underlying data distribution itself, hence sufficient data can be generated to alleviate the issue of overfitting.
Extracting Kinship from Obituary to Enhance Electronic Health Records for Genetic Research
Claims database and electronic health records database do not usually capture kinship or family relationship information, which is imperative for genetic research.
