AIMC Topic: Deep Learning

Clear Filters Showing 15361 to 15370 of 28423 articles

3D Kinect Camera Scheme with Time-Series Deep-Learning Algorithms for Classification and Prediction of Lung Tumor Motility.

Sensors (Basel, Switzerland)
This paper proposes a time-series deep-learning 3D Kinect camera scheme to classify the respiratory phases with a lung tumor and predict the lung tumor displacement. Specifically, the proposed scheme is driven by two time-series deep-learning algorit...

DGCyTOF: Deep learning with graphic cluster visualization to predict cell types of single cell mass cytometry data.

PLoS computational biology
Single-cell mass cytometry, also known as cytometry by time of flight (CyTOF) is a powerful high-throughput technology that allows analysis of up to 50 protein markers per cell for the quantification and classification of single cells. Traditional ma...

Optimization and Evaluation of an Intelligent Short-Term Blood Glucose Prediction Model Based on Noninvasive Monitoring and Deep Learning Techniques.

Journal of healthcare engineering
Continuous noninvasive blood glucose monitoring and estimation management by using photoplethysmography (PPG) technology always have a series of problems, such as substantial time variability, inaccuracy, and complex nonlinearity. This paper proposes...

COV-DLS: Prediction of COVID-19 from X-Rays Using Enhanced Deep Transfer Learning Techniques.

Journal of healthcare engineering
In this paper, modifications in neoteric architectures such as VGG16, VGG19, ResNet50, and InceptionV3 are proposed for the classification of COVID-19 using chest X-rays. The proposed architectures termed "COV-DLS" consist of two phases: heading mode...

Approaching automated applicator digitization from a new angle: Using sagittal images to improve deep learning accuracy and robustness in high-dose-rate prostate brachytherapy.

Brachytherapy
PURPOSE: To automate the segmentation of treatment applicators on computed tomography (CT) images for high-dose-rate (HDR) brachytherapy prostate patients implanted with titanium needles with the goals of improving plan quality and reducing the patie...

Mitigating transmit-B artifacts by predicting parallel transmission images with deep learning: A feasibility study using high-resolution whole-brain diffusion at 7 Tesla.

Magnetic resonance in medicine
PURPOSE: To propose a novel deep learning (DL) approach to transmit-B (B )-artifact mitigation without direct use of parallel transmission (pTx), by predicting pTx images from single-channel transmission (sTx) images.

Analysing Hate Speech against Migrants and Women through Tweets Using Ensembled Deep Learning Model.

Computational intelligence and neuroscience
Twitter's popularity has exploded in the previous few years, making it one of the most widely used social media sites. As a result of this development, the strategies described in this study are now more beneficial. Additionally, there has been an in...

Deep learning-assisted smartphone-based molecularly imprinted electrochemiluminescence detection sensing platform: Protable device and visual monitoring furosemide.

Biosensors & bioelectronics
A novel, portable, and smartphone-based molecularly imprinted polymer electrochemiluminescence (MIP-ECL) sensing platform was constructed for sensitive and selective determination of furosemide (FSM). In this platform, MoSe nanoparticles/starch-deriv...

Deep learning based object tracking for 3D microstructure reconstruction.

Methods (San Diego, Calif.)
In medical and material science, 3D reconstruction is of great importance for quantitative analysis of microstructures. After the image segmentation process of serial slices, in order to reconstruct each local structure in volume data, it needs to us...

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

Clinical radiology
AIM: To evaluate a novel deep-learning denoising method for ultra-low dose CT (ULDCT) in the assessment of coronary artery calcium score (CACS).