Medicare

Integrating scRNA-seq and scATAC-seq with inter-type attention heterogeneous graph neural networks.

Single-cell multi-omics techniques, which enable the simultaneous measurement of multiple modalities such as RNA gene expression and Assay for Transposase-Accessible Chromatin (ATAC) within individual cells, have become a powerful tool for deciphering the intricate complexity of cellular systems. Most current methods rely on motif databases to establish cross-modality relationships between genes f...

A Novel Automatic Real-time Motion Tracking Method for Magnetic Resonance Imaging-guided Radiotherapy: Leveraging the Enhanced Tracking-Learning-Detection Framework with Automatic Segmentation

Background and Purpose: Accurate motion tracking in MRI-guided Radiotherapy (MRIgRT) is essential for effective treatment delivery. This study aimed to enhance motion tracking precision in MRIgRT through an automatic real-time markerless tracking method using an enhanced Tracking-Learning-Detection (ETLD) framework with automatic segmentation. Materials and Methods: We developed a novel MRIgRT m...

Artificial Intelligence Driven Course Generation: A Case Study Using ChatGPT

This study explores Artificial Intelligence use, specifically ChatGPT, in creating educational content. The study aims to elaborate on using ChatGPT...

Deep learning assisted quantitative analysis of Aβ and microglia in patients with idiopathic normal pressure hydrocephalus in relation to cognitive outcome.

Neuropathologic changes of Alzheimer disease (AD) including Aβ accumulation and neuroinflammation are frequently observed in the cerebral cortex of pa...

3D-ViTac: Learning Fine-Grained Manipulation with Visuo-Tactile Sensing

Tactile and visual perception are both crucial for humans to perform fine-grained interactions with their environment. Developing similar multi-moda...

Taming the Long Tail in Human Mobility Prediction

With the popularity of location-based services, human mobility prediction plays a key role in enhancing personalized navigation, optimizing recommen...

ReMEmbR: Building and Reasoning Over Long-Horizon Spatio-Temporal Memory for Robot Navigation

Navigating and understanding complex environments over extended periods of time is a significant challenge for robots. People interacting with the r...

LoRa Communication for Agriculture 4.0: Opportunities, Challenges, and Future Directions

The emerging field of smart agriculture leverages the Internet of Things (IoT) to revolutionize farming practices. This paper investigates the trans...

Refinement of genetic variants needs attention

Variant calling refinement is crucial for distinguishing true genetic variants from technical artifacts in high-throughput sequencing data. Manual r...

How Should Medicare Pay for Artificial Intelligence?

Covering a Graph with Dense Subgraph Families, via Triangle-Rich Sets

Graphs are a fundamental data structure used to represent relationships in domains as diverse as the social sciences, bioinformatics, cybersecurity,...

Analysis of 3GPP and Ray-Tracing Based Channel Model for 5G Industrial Network Planning

Appropriate channel models tailored to the specific needs of industrial environments are crucial for the 5G private industrial network design and gu...

GUME: Graphs and User Modalities Enhancement for Long-Tail Multimodal Recommendation

Multimodal recommendation systems (MMRS) have received considerable attention from the research community due to their ability to jointly utilize in...

Machine learning for detection of heterogeneous effects of Medicaid coverage on depression.

In 2008, Oregon expanded its Medicaid program using a lottery, creating a rare opportunity to study the effects of Medicaid coverage using a randomize...

Using deep learning to improve the intelligibility of a target speaker in noisy multi-talker environments for people with normal hearing and hearing loss.

Understanding speech in noisy environments is a challenging task, especially in communication situations with several competing speakers. Despite thei...

Enhancing Hi-C contact matrices for loop detection with Capricorn: a multiview diffusion model.

MOTIVATION: High-resolution Hi-C contact matrices reveal the detailed three-dimensional architecture of the genome, but high-coverage experimental Hi-...

ALPHAGMUT: A Rationale-Guided Alpha Shape Graph Neural Network to Evaluate Mutation Effects

In silico methods evaluating the mutation effects of missense mutations are providing an important approach for understanding mutations in personal ...

Lower Extremity Growth according to AI Automated Femorotibial Length Measurement on Slot-Scanning Radiographs in Pediatric Patients.

Background Commonly used pediatric lower extremity growth standards are based on small, dated data sets. Artificial intelligence (AI) enables creation...

Understanding gut microbiome-based machine learning platforms: A review on therapeutic approaches using deep learning.

Human beings possess trillions of microbial cells in a symbiotic relationship. This relationship benefits both partners for a long time. The gut micro...

Deep Learning-based Fibrosis Extent on Computed Tomography Predicts Outcome of Fibrosing Interstitial Lung Disease Independent of Visually Assessed Computed Tomography Pattern.

Radiologic pattern has been shown to predict survival in patients with fibrosing interstitial lung disease. The additional prognostic value of fibros...