Results 191 to 200 of about 207,683 (286)

Polymerase Chain Reaction. Perturbation Theory and Machine Learning Artificial Intelligence‐Experimental Microbiome Analysis: Applications to Ancient DNA and Tree Soil Metagenomics Cases of Study

open access: yesAdvanced Intelligent Systems, EarlyView.
The polymerase chain reaction (PCR).Perturbation Theory and Machine Learning framework integrates perturbation theory and machine learning to classify genetic sequences, distinguishing ancient DNA from modern controls and predicting tree health from soil metagenomic data.
Jose L. Rodriguez   +19 more
wiley   +1 more source

RPSLearner: A Novel Approach Based on Random Projection and Deep Stacking Learning for Categorizing Non‐Small Cell Lung Cancer

open access: yesAdvanced Intelligent Systems, EarlyView.
Identifying non‐small cell lung cancer (NSCLC) subtypes is essential for precision cancer treatment. Conventional methods are laborious, or time‐consuming. To address these concerns, RPSLearner is proposed, which combines random projection and stacking ensemble learning for accurate NSCLC subtyping. RPSLearner outperforms state‐of‐the‐art approaches in
Xinchao Wu, Jieqiong Wang, Shibiao Wan
wiley   +1 more source

A Novel Contact‐Implicit Trajectory Optimization Framework for Quadruped Locomotion without Fixed Contact Sequences

open access: yesAdvanced Intelligent Systems, EarlyView.
Legged robots have advanced in environmental interaction through contact, but most works rely on fixed contact sequences. This work presents a new method based on an indirect optimization method for legged robots to automatically generate contact sequences for complex movements.
Yaowei Chen, Jie Zhang, Ming Lyu
wiley   +1 more source

RABEM: risk-adaptive Bayesian ensemble model for fraud detection. [PDF]

open access: yesSci Rep
Almarshad FA   +3 more
europepmc   +1 more source

Disentangling Coincident Cell Events Using Deep Transfer Learning and Compressive Sensing

open access: yesAdvanced Intelligent Systems, EarlyView.
Overlapping cells during detection distort single‐cell measurements and reduce diagnostic accuracy. A hybrid framework combining a fully convolutional neural network with compressive sensing to disentangle overlapping signals directly from raw time‐series data is presented.
Moritz Leuthner   +2 more
wiley   +1 more source

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