Alexandros Karargyris,Renato Umeton,Micah J Sheller et al.
Alexandros Karargyris et al.
Medical artificial intelligence (AI) has tremendous potential to advance healthcare by supporting and contributing to the evidence-based practice of medicine, personalizing patient treatment, reducing costs, and improving both healthcare pr...
Rapid online learning and robust recall in a neuromorphic olfactory circuit [0.03%]
类神经嗅觉电路的快速在线学习和稳健回忆
Nabil Imam,Thomas A Cleland
Nabil Imam
We present a neural algorithm for the rapid online learning and identification of odourant samples under noise, based on the architecture of the mammalian olfactory bulb and implemented on the Intel Loihi neuromorphic system. As with biolog...
Pandemic data challenges [0.03%]
新冠疫情数据挑战
The worldwide outbreak of COVID-19 has led to great tragedy and poses unprecedented challenges for countries' healthcare systems. Data has become an important instrument in the global fight against the unprecedented spread of the virus. But...
[This corrects the article DOI: 10.1038/s42256-020-0172-7.]. © The Author(s), under exclusive licence to Springer Nature Limited 2020.
Published Erratum
Nature machine intelligence. 2020;2(5):289. DOI:10.1038/s42256-020-0179-0 2020
Suraj Pai,Dennis Bontempi,Ibrahim Hadzic et al.
Suraj Pai et al.
Foundation models in deep learning are characterized by a single large-scale model trained on vast amounts of data serving as the foundation for various downstream tasks. Foundation models are generally trained using self-supervised learnin...
Unsupervised ensemble-based phenotyping enhances discoverability of genes related to left-ventricular morphology [0.03%]
无监督集成表型分析增强与左心室形态相关基因的可发现性
Rodrigo Bonazzola,Enzo Ferrante,Nishant Ravikumar et al.
Rodrigo Bonazzola et al.
Recent genome-wide association studies have successfully identified associations between genetic variants and simple cardiac morphological parameters derived from cardiac magnetic resonance images. However, the emergence of large databases,...
Synthetic data accelerates the development of generalizable learning-based algorithms for X-ray image analysis [0.03%]
合成数据加速基于学习的算法在X射线图像分析中的通用性发展
Cong Gao,Benjamin D Killeen,Yicheng Hu et al.
Cong Gao et al.
Artificial intelligence (AI) now enables automated interpretation of medical images. However, AI's potential use for interventional image analysis remains largely untapped. This is because the post hoc analysis of data collected during live...
Guo-Wei Wei
Guo-Wei Wei
DeepMind's AlphaFold recently demonstrated the potential of deep learning for protein structure prediction. DeepFragLib, a new protein-specific fragment library built using deep neural networks, may have advanced the field to the next stage...
FDA Fosters Innovative Approaches in Research, Resources, and Collaboration [0.03%]
FDA 推动研究、资源和合作中的创新方法
Brandon D Gallas,Aldo Badano,Sarah Dudgeon et al.
Brandon D Gallas et al.
Weak signal extraction enabled by deep neural network denoising of diffraction data [0.03%]
深度神经网络对衍射数据的去噪可实现弱信号提取
Jens Oppliger,M Michael Denner,Julia Küspert et al.
Jens Oppliger et al.
The removal or cancellation of noise has wide-spread applications in imaging and acoustics. In applications in everyday life, such as image restoration, denoising may even include generative aspects, which are unfaithful to the ground truth...