Results 121 to 130 of about 2,007,558 (136)

Transforming Healthcare with Nanomedicine: A SWOT Analysis of Drug Delivery Innovation

open access: yesDrug Design, Development and Therapy
Hao Zhang,1 Suping Li,1 Xingming Ma2 1Department of Nuclear Medicine, Affiliated Hospital of North Sichuan Medical College North Sichuan Medical College, Nanchong, 637000, People’s Republic of China; 2School of Health Management, Xihua University ...
Zhang H, Li S, Ma X
doaj  

A review on selenium nanoparticles and their biomedical applications

open access: yesBiomedical Technology
K. Karthik   +3 more
semanticscholar   +1 more source

The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration

open access: yesNature Biotechnology, 2007
Barry Smith   +17 more
semanticscholar   +1 more source

The ImageJ ecosystem: An open platform for biomedical image analysis

open access: yesMolecular Reproduction and Development, 2015
J. Schindelin   +3 more
semanticscholar   +1 more source

U-Net: Convolutional Networks for Biomedical Image Segmentation

International Conference on Medical Image Computing and Computer-Assisted Intervention, 2015
There is large consent that successful training of deep networks requires many thousand annotated training samples. In this paper, we present a network and training strategy that relies on the strong use of data augmentation to use the available ...
O. Ronneberger, P. Fischer, T. Brox
semanticscholar   +1 more source

A generalist vision–language foundation model for diverse biomedical tasks

Nature Medicine, 2023
Traditional biomedical artificial intelligence (AI) models, designed for specific tasks or modalities, often exhibit limited flexibility in real-world deployment and struggle to utilize holistic information.
Kai Zhang   +15 more
semanticscholar   +1 more source

U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation

arXiv.org
Convolutional Neural Networks (CNNs) and Transformers have been the most popular architectures for biomedical image segmentation, but both of them have limited ability to handle long-range dependencies because of inherent locality or computational ...
Jun Ma, Feifei Li, Bo Wang
semanticscholar   +1 more source

Empowering Biomedical Discovery with AI Agents

Cell
We envision "AI scientists" as systems capable of skeptical learning and reasoning that empower biomedical research through collaborative agents that integrate AI models and biomedical tools with experimental platforms.
Shanghua Gao   +8 more
semanticscholar   +1 more source

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