Detecting Chemotherapeutic Skin Adverse Reactions in Social Health Networks Using Deep Learning
Sign Up to like & getrecommendations! Published in 2018 at "JAMA Oncology"
DOI: 10.1001/jamaoncol.2017.5688
Abstract: This study reports proof-of-principle early detection of chemotherapeutic-associated skin adverse drug reactions from social health networks using a deep learning–based signal generation pipeline to capture how patients describe cutaneous eruptions. read more here.
Keywords: reactions social; networks using; using deep; social health ... See more keywords
Using deep autoencoders to identify abnormal brain structural patterns in neuropsychiatric disorders: A large‐scale multi‐sample study
Sign Up to like & getrecommendations! Published in 2019 at "Human Brain Mapping"
DOI: 10.1002/hbm.24423
Abstract: Machine learning is becoming an increasingly popular approach for investigating spatially distributed and subtle neuroanatomical alterations in brain‐based disorders. However, some machine learning models have been criticized for requiring a large number of cases in… read more here.
Keywords: using deep; autoencoders identify; model; deep autoencoders ... See more keywords
Generation of synthetic megavoltage CT for MRI-only radiotherapy treatment planning using a 3D deep convolutional neural network.
Sign Up to like & getrecommendations! Published in 2022 at "Medical physics"
DOI: 10.1002/mp.15876
Abstract: BACKGROUND Megavoltage computed tomography (MVCT) has been implemented on many radiotherapy treatment machines for on-board anatomical visualization, localization, and adaptive dose calculation. Implementing an MR-only workflow by synthesizing MVCT from MRI would offer numerous advantages… read more here.
Keywords: neural network; mvct; treatment planning; mri ... See more keywords
Parallel imaging in time‐of‐flight magnetic resonance angiography using deep multistream convolutional neural networks
Sign Up to like & getrecommendations! Published in 2019 at "Magnetic Resonance in Medicine"
DOI: 10.1002/mrm.27656
Abstract: To develop and evaluate a method of parallel imaging time‐of‐flight (TOF) MRA using deep multistream convolutional neural networks (CNNs). read more here.
Keywords: deep multistream; using deep; multistream convolutional; time flight ... See more keywords
Rapid estimation of 2D relative B1+ ‐maps from localizers in the human heart at 7T using deep learning
Sign Up to like & getrecommendations! Published in 2022 at "Magnetic Resonance in Medicine"
DOI: 10.1002/mrm.29510
Abstract: Subject‐tailored parallel transmission pulses for ultra‐high fields body applications are typically calculated based on subject‐specific B1+$$ {\mathrm{B}}_1^{+} $$ ‐maps of all transmit channels, which require lengthy adjustment times. This study investigates the feasibility of using… read more here.
Keywords: estimation relative; relative maps; rapid estimation; deep learning ... See more keywords
Diagnosis of Viral Diseases Using Deep Sequencing and Metagenomics Analyses.
Sign Up to like & getrecommendations! Published in 2022 at "Methods in molecular biology"
DOI: 10.1007/978-1-0716-1835-6_22
Abstract: Viruses are ubiquitous in nature and exist in a variety of habitats. The advancement in sequencing technologies has revolutionized the understanding of viral biodiversity associated with plant diseases. Deep sequencing combined with metagenomics is a… read more here.
Keywords: deep sequencing; using deep; sequencing; diseases using ... See more keywords
Detection of difficult airway using deep learning
Sign Up to like & getrecommendations! Published in 2020 at "Machine Vision and Applications"
DOI: 10.1007/s00138-019-01055-3
Abstract: Whenever a patient needs to enter the operating room, in case the surgery requires general anesthesia, he/she must be intubated, and an anesthesiologist has to make a previous check to the patient in order to… read more here.
Keywords: using deep; deep learning; detection difficult; difficult airway ... See more keywords
Whole-body voxel-based internal dosimetry using deep learning
Sign Up to like & getrecommendations! Published in 2020 at "European Journal of Nuclear Medicine and Molecular Imaging"
DOI: 10.1007/s00259-020-05013-4
Abstract: In the era of precision medicine, patient-specific dose calculation using Monte Carlo (MC) simulations is deemed the gold standard technique for risk-benefit analysis of radiation hazards and correlation with patient outcome. Hence, we propose a… read more here.
Keywords: medicine; using deep; anatomy; dosimetry ... See more keywords
Automated detection and delineation of hepatocellular carcinoma on multiphasic contrast-enhanced MRI using deep learning
Sign Up to like & getrecommendations! Published in 2020 at "Abdominal Radiology"
DOI: 10.1007/s00261-020-02604-5
Abstract: Purpose Liver Imaging Reporting and Data System (LI-RADS) uses multiphasic contrast-enhanced imaging for hepatocellular carcinoma (HCC) diagnosis. The goal of this feasibility study was to establish a proof-of-principle concept towards automating the application of LI-RADS,… read more here.
Keywords: hepatocellular carcinoma; using deep; deep learning; multiphasic contrast ... See more keywords
Detection and Labeling of Vertebrae in MR Images Using Deep Learning with Clinical Annotations as Training Data
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Digital Imaging"
DOI: 10.1007/s10278-017-9945-x
Abstract: The purpose of this study was to investigate the potential of using clinically provided spine label annotations stored in a single institution image archive as training data for deep learning-based vertebral detection and labeling pipelines.… read more here.
Keywords: detection; image; training data; using deep ... See more keywords
Rapid Assessment of Acute Ischemic Stroke by Computed Tomography Using Deep Convolutional Neural Networks
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Digital Imaging"
DOI: 10.1007/s10278-021-00457-y
Abstract: Acute stroke is one of the leading causes of disability and death worldwide. Regarding clinical diagnoses, a rapid and accurate procedure is necessary for patients suffering from acute stroke. This study proposes an automatic identification… read more here.
Keywords: ischemic stroke; using deep; deep convolutional; convolutional neural ... See more keywords