Large language models are transforming microbiome research by enabling advanced sequence profiling, functional prediction, and association mining across complex datasets. They automate microbial classification and disease‐state recognition, improving cross‐study integration and clinical diagnostics.
Jieqi Xing +4 more
wiley +1 more source
A manta ray-bayesian optimization approach for hyperparameter-tuned convolutional neural networks in lung cancer classification. [PDF]
Samal S +5 more
europepmc +1 more source
Interval Prediction of Remaining Useful Life Based on Uncertainty Quantification with Bayesian Convolutional Neural Networks Featuring Dual-Output Units. [PDF]
Qu Z, He J, Liu Y, Mao S, Han X.
europepmc +1 more source
Convolutional neural networks using preoperative CT to predict short-term recurrence after incisional hernia repair. [PDF]
Xing X, Zhao B, Wang M, Liu Y.
europepmc +1 more source
Automated Identification of Accessory Mental Foramen Using Cone-Beam Computed Tomography and Convolutional Neural Networks. [PDF]
Ovuz Z, Gursu Sahin E, Etem T.
europepmc +1 more source
Efficient convolutional neural networks for acute lymphoblastic leukaemia prediction in computer vision. [PDF]
Mohan SB +4 more
europepmc +1 more source
Correction for Anand et al., Convolutional neural networks outperform other presence-only species distribution modeling algorithms. [PDF]
europepmc +1 more source
Related searches:
Factorized Convolutional Neural Networks
2017 IEEE International Conference on Computer Vision Workshops (ICCVW), 2017In this paper, we propose to factorize the convolutional layer to reduce its computation. The 3D convolution operation in a convolutional layer can be considered as performing spatial convolution in each channel and linear projection across channels simultaneously.
Wang, Min, Liu, Baoyuan, Foroosh, Hassan
openaire +3 more sources

