Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9366876PMC
http://dx.doi.org/10.1016/j.xjtc.2022.05.015DOI Listing

Publication Analysis

Top Keywords

novel modular
4
modular inner
4
inner aortic
4
aortic arch
4
arch stent-graft
4
stent-graft localized
4
localized stanford
4
stanford type
4
type aortic
4
aortic dissection
4

Similar Publications

Using -rhizobia- interaction networks, we address first the soil invasion success of , and second, we report either -rhizobia partnership should form an isolated module within the symbiosis interaction network. Different indexes were used to determine model invasion success and the network topology. Our results indicated that invasion decreased soil microbial biomass, basal respiration, and enzymatic activities.

View Article and Find Full Text PDF

Characterizing brain dynamic functional connectivity (dFC) patterns from functional Magnetic Resonance Imaging (fMRI) data is of paramount importance in neuroscience and medicine. Recently, many graph neural network (GNN) models, combined with transformers or recurrent neural networks (RNNs), have shown great potential for modeling the dFC patterns. However, these methods face challenges in effectively characterizing the modularity organization of brain networks and capturing varying dFC state patterns.

View Article and Find Full Text PDF

It is now possible to generate large volumes of high-quality images of biomolecules at near-atomic resolution and in near-native states using cryogenic electron microscopy/electron tomography (Cryo-EM/ET). However, the precise annotation of structures like filaments and membranes remains a major barrier towards applying these methods in high-throughput. To address this, we present TARDIS ( ransformer-b sed apid imensionless nstance egmentation), a machine-learning framework for fast and accurate annotation of micrographs and tomograms.

View Article and Find Full Text PDF

Precise volumetric measurement of newly formed bone after maxillary sinus floor augmentation (MSFA) can help clinicians in planning for dental implants. This study aimed to introduce a novel modular framework to facilitate volumetric calculations based on manually drawn segmentations of user-defined areas of interest on cone-beam computed tomography (CBCT) images MATERIAL & METHODS: Two interconnected networks for manual segmentation of a defined volume of interest and dental implant volume calculation, respectively, were used in parallel. The volume data of dental implant manufacturers were used for reference.

View Article and Find Full Text PDF

Background: The increasing use of social media to share lived and living experiences of substance use presents a unique opportunity to obtain information on side effects, use patterns, and opinions on novel psychoactive substances. However, due to the large volume of data, obtaining useful insights through natural language processing technologies such as large language models is challenging.

Objective: This paper aims to develop a retrieval-augmented generation (RAG) architecture for medical question answering pertaining to clinicians' queries on emerging issues associated with health-related topics, using user-generated medical information on social media.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!