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An Infrared Array Sensor-Based Approach for Activity Detection, Combining Low-Cost Technology with Advanced Deep Learning Techniques.

In this paper, we propose an activity detection system using a 24 × 32 resolution infrared array sen...

A new technique for robotic lateral pelvic lymph node dissection for advanced low rectal cancer with emphasis on en bloc resection and inferior vesical vessel preservation.

BACKGROUND: Lateral pelvic lymph node (LPLN) dissection is becoming increasingly important in the tr...

Rapid prototyping of ion-selective electrodes using a low-cost 3D printed internet-of-things (IoT) controlled robot.

We report automated fabrication of solid-contact sodium-selective (Na-ISEs) and potassium-selective ...

Road Surface Anomaly Assessment Using Low-Cost Accelerometers: A Machine Learning Approach.

Roads are a strategic asset of a country and are of great importance for the movement of passengers ...

End-to-end deep learning for interior tomography with low-dose x-ray CT.

There are several x-ray computed tomography (CT) scanning strategies used to reduce radiation dose, ...

Effective high-to-low-level feature aggregation network for endoscopic image classification.

PURPOSE: The accuracy improvement in endoscopic image classification matters to the endoscopists in ...

MultiHeadGAN: A deep learning method for low contrast retinal pigment epithelium cell segmentation with fluorescent flatmount microscopy images.

BACKGROUND: Retinal pigment epithelium (RPE) aging is an important cause of vision loss. As RPE agin...

Automated rare sperm identification from low-magnification microscopy images of dissociated microsurgical testicular sperm extraction samples using deep learning.

OBJECTIVE: To develop a machine learning algorithm to detect rare human sperm in semen and microsurg...

The Curative Effect of Pregabalin in the Treatment of Postherpetic Neuralgia Analyzed by Deep Learning-Based Brain Resting-State Functional Magnetic Resonance Images.

This work aimed to investigate the brain resting-state functional magnetic resonance imaging (fMRI) ...

MRCON-Net: Multiscale reweighted convolutional coding neural network for low-dose CT imaging.

BACKGROUND AND OBJECTIVE: Low-dose computed tomography (LDCT) has become increasingly important for ...

Pulmonary emphysema quantification at low dose chest CT using Deep Learning image reconstruction.

PURPOSE: Quantitative analysis of emphysema volume is affected by the radiation dose and the CT reco...

Nonideality-Aware Training for Accurate and Robust Low-Power Memristive Neural Networks.

Recent years have seen a rapid rise of artificial neural networks being employed in a number of cogn...

Very low-volume interval training improves nonalcoholic fatty liver disease fibrosis score and cardiometabolic health in adults with obesity and metabolic syndrome.

Non-alcoholic fatty liver disease (NAFLD) and cardiometabolic disorders are highly prevalent in obes...

Machine learning prediction of gestational age from metabolic screening markers resistant to ambient temperature transportation: Facilitating use of this technology in low resource settings of South Asia and East Africa.

BACKGROUND: Knowledge of gestational age is critical for guiding preterm neonatal care. In the last ...

Deep learning applications for the accurate identification of low-transcriptional activity drugs and their mechanism of actions.

Analysis of drug-induced expression profiles facilitated comprehensive understanding of drug propert...

Deep learning-based single image super-resolution for low-field MR brain images.

Low-field MRI scanners are significantly less expensive than their high-field counterparts, which gi...

Pseudo low-energy monochromatic imaging of head and neck cancers: Deep learning image reconstruction with dual-energy CT.

PURPOSE: Low-energy virtual monochromatic images (VMIs) derived from dual-energy computed tomography...

A deep-learning method for the denoising of ultra-low dose chest CT in coronary artery calcium score evaluation.

AIM: To evaluate a novel deep-learning denoising method for ultra-low dose CT (ULDCT) in the assessm...

Early experience with total robotic D2 gastrectomy in a low incidence region: surgical perspectives.

BACKGROUND: Few European centers have reported on robotic gastrectomy for malignancy. We report our ...

Pros and Cons of Applying Deep Learning Automatic Scan-Range Adjustment to Low-Dose Chest CT in Lung Cancer Screening Programs.

A low-cost approach for soil moisture prediction using multi-sensor data and machine learning algorithm.

A high-resolution soil moisture prediction method has recently gained its importance in various fiel...