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Robotic low anterior resection for locally advanced rectal cancer - A video vignette.

Development of deep learning-assisted overscan decision algorithm in low-dose chest CT: Application to lung cancer screening in Korean National CT accreditation program.

We propose a deep learning-assisted overscan decision algorithm in chest low-dose computed tomograph...

Accelerated Discovery of Ternary Gold Alloy Materials with Low Resistivity via an Interpretable Machine Learning Strategy.

New ternary gold alloys with low resistivities (ρ) were screened out via an interpretable machine le...

Robotic low anterior resection with liver wedge metastasectomy.

Detectability of Small Low-Attenuation Lesions With Deep Learning CT Image Reconstruction: A 24-Reader Phantom Study.

Iterative reconstruction (IR) techniques are susceptible to contrast-dependent spatial resolution, ...

Quantization-aware training for low precision photonic neural networks.

Recent advances in Deep Learning (DL) fueled the interest in developing neuromorphic hardware accele...

Auto3D: Automatic Generation of the Low-Energy 3D Structures with ANI Neural Network Potentials.

Computational programs accelerate the chemical discovery processes but often need proper three-dimen...

Biopolymer based artificial synapses enable linear conductance tuning and low-power for neuromorphic computing.

Neuromorphic computing is considered a promising method for resolving the traditional von Neumann bo...

Effective Training of Convolutional Neural Networks With Low-Bitwidth Weights and Activations.

This paper tackles the problem of training a deep convolutional neural network of both low-bitwidth ...

Automated Identification of Clinical Procedures in Free-Text Electronic Clinical Records with a Low-Code Named Entity Recognition Workflow.

BACKGROUND: Clinical procedures are often performed in outpatient clinics without prior scheduling a...

Wavelet subband-specific learning for low-dose computed tomography denoising.

Deep neural networks have shown great improvements in low-dose computed tomography (CT) denoising. E...

Low precision decentralized distributed training over IID and non-IID data.

Decentralized distributed learning is the key to enabling large-scale machine learning (training) on...

Imbalanced low-rank tensor completion via latent matrix factorization.

Tensor completion has been widely used in computer vision and machine learning. Most existing tensor...

A deep learning approach to generate synthetic CT in low field MR-guided radiotherapy for lung cases.

INTRODUCTION: This study aims to apply a conditional Generative Adversarial Network (cGAN) to genera...

Lightweight Deep Learning Classification Model for Identifying Low-Resolution CT Images of Lung Cancer.

With an astounding five million fatal cases every year, lung cancer is among the leading causes of m...

Correlated RNN Framework to Quickly Generate Molecules with Desired Properties for Energetic Materials in the Low Data Regime.

Motivated by the challenging of deep learning on the low data regime and the urgent demand for intel...

Product Identification in the Low-Temperature Oxidation of Cyclohexane Using a Jet-Stirred Reactor in Combination with SVUV-PEPICO Analysis and Theoretical Quantum Calculations.

Cyclohexane oxidation chemistry was investigated using a near-atmospheric pressure jet-stirred react...

mRNAsi-related metabolic risk score model identifies poor prognosis, immunoevasive contexture, and low chemotherapy response in colorectal cancer patients through machine learning.

Colorectal cancer (CRC) is one of the most fatal cancers of the digestive system. Although cancer st...

Field validation of deep learning based Point-of-Care device for early detection of oral malignant and potentially malignant disorders.

Early detection of oral cancer in low-resource settings necessitates a Point-of-Care screening tool ...

Swin-MFA: A Multi-Modal Fusion Attention Network Based on Swin-Transformer for Low-Light Image Human Segmentation.

In recent years, image segmentation based on deep learning has been widely used in medical imaging, ...

Deep learning based correction of low performing pixel in computed tomography.

Low Performing Pixel (LPP)/bad pixel in CT detectors cause ring and streaks artifacts, structured no...