Using Machine Learning to Measure Relatedness Between Genes: A Multi-Features Model Yan Wang, Sen Yang, Jing Zhao, Wei Du, Yanchun Liang, Cankun Wang, Fengfeng Zhou, Yuan Tian & Qin Ma Scientific Reports volume 9, Article number: 4192 (2019) Cite this article 5829 Accesses...
Deep-learning models trained on retinal fundus images can be used to identify chronic kidney disease and type 2 diabetes and to predict the risk of the progression of these diseases. Kang Zhang Xiaohong Liu Guangyu Wang Article15 Jun 2021Nature Biomedical Engineering ...
Generally, oxygen uptake measurements are collected during maximum effort activity on a treadmill or a cycle ergometer [3]. These maximal tests directly measure VO2 max with high accuracy but are expensive, requiring fixed, controlled protocol and trained personnel. These tests also pose several ...
If you wanted to know your speed at a particular instant, you would have to measure the change in speed that occurs over a set period of time. By making that set period smaller and smaller, you could reasonably estimate the speed at that instant. In effect, as you make the change in ...
Being so prone to such volatility in crop yield, this type of technology opens up a world of opportunities for greater productivity—and sustainability. Pepe Cafferata, Head of QuantumBlack, Latin America The predictive model uses data to measure the efficiency of salmon converting feed ...
(early, late, and pooled) to measure the individual impact of each feature on the model outcome. With the combination of classification accuracy and SHAP values, we were able to validate each measure’s ability to discriminate STZ rats from controls. As SHAP values are instance-based, they ...
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Improvements in the manufacture of bottles to contain gases under pressure, such as oxygen, hydrogen, carbon dioxide or any other gas, characterized in that the body of the bottle is constituted by successive layers of glass fibers reinforced with polyester, subjecting the assembly to polymerization...
respectively. Second, the supervised methods (e.g., supporting vector regression (SVR)) based on Monte Carlo simulations were applied to the same dataset to “predict” atmospheric oxygen levels since 4.0 Ga quantitatively. Our independent method successfully revealed a high-resolution two-step pat...
The similarity measure is the heart of the active-learning algorithm, determining whether a new structure should be added to the training set and ensuring a balanced representation of different regions of the phase space. Notably, this work introduces an additional measure, Dmax, which, though ...