Reconstructing Kinetic Models for Dynamical Studies of Metabolism using Generative Adversarial Networks [0.03%]
基于生成对抗网络的代谢动力学模型重建及其动态研究
Subham Choudhury,Michael Moret,Pierre Salvy et al.
Subham Choudhury et al.
Kinetic models of metabolism relate metabolic fluxes, metabolite concentrations and enzyme levels through mechanistic relations, rendering them essential for understanding, predicting and optimizing the behaviour of living organisms. Howeve...
Deep learning-based robust positioning for all-weather autonomous driving [0.03%]
基于深度学习的全天候自动驾驶稳健定位方法研究
Yasin Almalioglu,Mehmet Turan,Niki Trigoni et al.
Yasin Almalioglu et al.
Interest in autonomous vehicles (AVs) is growing at a rapid pace due to increased convenience, safety benefits and potential environmental gains. Although several leading AV companies predicted that AVs would be on the road by 2020, they ar...
Ramon Viñas,Chaitanya K Joshi,Dobrik Georgiev et al.
Ramon Viñas et al.
Integrating gene expression across tissues and cell types is crucial for understanding the coordinated biological mechanisms that drive disease and characterise homeostasis. However, traditional multitissue integration methods cannot handle...
Multimodal data fusion for cancer biomarker discovery with deep learning [0.03%]
基于深度学习的癌症生物标志物多模态数据融合发现方法研究
Sandra Steyaert,Marija Pizurica,Divya Nagaraj et al.
Sandra Steyaert et al.
Technological advances now make it possible to study a patient from multiple angles with high-dimensional, high-throughput multi-scale biomedical data. In oncology, massive amounts of data are being generated ranging from molecular, histopa...
Resolution enhancement with a task-assisted GAN to guide optical nanoscopy image analysis and acquisition [0.03%]
任务辅助型生成对抗网络引导光学纳米显微图像解析与获取以增强分辨率
Catherine Bouchard,Theresa Wiesner,Andréanne Deschênes et al.
Catherine Bouchard et al.
Super-resolution fluorescence microscopy methods enable the characterization of nanostructures in living and fixed biological tissues. However, they require the adjustment of multiple imaging parameters while attempting to satisfy conflicti...
Algorithmic fairness and bias mitigation for clinical machine learning with deep reinforcement learning [0.03%]
基于深度强化学习的临床机器学习中的算法公平性与偏差缓解
Jenny Yang,Andrew A S Soltan,David W Eyre et al.
Jenny Yang et al.
As models based on machine learning continue to be developed for healthcare applications, greater effort is needed to ensure that these technologies do not reflect or exacerbate any unwanted or discriminatory biases that may be present in t...
Prediction of mechanistic subtypes of Parkinson's using patient-derived stem cell models [0.03%]
利用患者诱导多能干细胞模型预测帕金森病的病因亚型
Karishma D&#x;Sa,James R Evans,Gurvir S Virdi et al.
Karishma D&#x;Sa et al.
Parkinson's disease is a common, incurable neurodegenerative disorder that is clinically heterogeneous: it is likely that different cellular mechanisms drive the pathology in different individuals. So far it has not been possible to define ...
Translating Intersectionality to Fair Machine Learning in Health Sciences [0.03%]
从健康科学的角度将交又性理论转化为公平的机器学习
Elle Lett,William G La Cava
Elle Lett
Fairness approaches in machine learning should involve more than assessment of performance metrics across groups. Shifting the focus away from model metrics, we reframe fairness through the lens of intersectionality, a Black feminist theore...
Erratum: Author Correction: Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence [0.03%]
新冠诊断的隐私保护协作人工智能方法研究误报修正通知
Xiang Bai,Hanchen Wang,Liya Ma et al.
Xiang Bai et al.
[This corrects the article DOI: 10.1038/s42256-021-00421-z.]. Keywords: Computational science; Health care; ...
Published Erratum
Nature machine intelligence. 2022;4(4):413. DOI:10.1038/s42256-022-00485-5 2022
Predicting functional effect of missense variants using graph attention neural networks [0.03%]
基于图注意力神经网络的错义变异功能效应预测模型
Haicang Zhang,Michelle S Xu,Xiao Fan et al.
Haicang Zhang et al.
Accurate prediction of damaging missense variants is critically important for interpreting a genome sequence. Although many methods have been developed, their performance has been limited. Recent advances in machine learning and the availab...