Automated detection and characterization of harmonic tremor in continuous seismic data
Sign Up to like & getrecommendations! Published in 2017 at "Geophysical Research Letters"
DOI: 10.1002/2017gl073715
Abstract: Harmonic tremor is a common feature of volcanic, hydrothermal, and ice-sheet seismicity, and is thus an important proxy for monitoring changes in these systems. However, no automated methods for detecting harmonic tremor currently exist. Because… read more here.
Keywords: harmonic tremor; automated detection; detection characterization; seismic data ... See more keywords
Evaluating new technology for biodiversity monitoring: Are drone surveys biased?
Sign Up to like & getrecommendations! Published in 2021 at "Ecology and Evolution"
DOI: 10.1002/ece3.7518
Abstract: Abstract Drones and machine learning‐based automated detection methods are being used by ecologists to conduct wildlife surveys with increasing frequency. When traditional survey methods have been evaluated, a range of factors have been found to… read more here.
Keywords: detection; ground; drone; automated detection ... See more keywords
Improved automated detection of glaucoma by correlating fundus and SD‐OCT image analysis
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22413
Abstract: Glaucoma is a multifactorial ocular disease. Ophthalmologists mostly use fundus or optical coherence tomography (OCT) for diagnosis of glaucoma. In this study, a hybrid computer‐aided‐diagnosis (H‐CAD) system has been proposed that integrates both fundus and… read more here.
Keywords: fundus oct; automated detection; cad system; glaucoma ... See more keywords
Automated Detection of Brain Metastases on T1‐Weighted MRI Using a Convolutional Neural Network: Impact of Volume Aware Loss and Sampling Strategy
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Magnetic Resonance Imaging"
DOI: 10.1002/jmri.28274
Abstract: Detection of brain metastases (BM) and segmentation for treatment planning could be optimized with machine learning methods. Convolutional neural networks (CNNs) are promising, but their trade‐offs between sensitivity and precision frequently lead to missing small… read more here.
Keywords: automated detection; brain metastases; detection brain; convolutional neural ... See more keywords
Automated detection of exudative age-related macular degeneration in spectral domain optical coherence tomography using deep learning
Sign Up to like & getrecommendations! Published in 2017 at "Graefe's Archive for Clinical and Experimental Ophthalmology"
DOI: 10.1007/s00417-017-3850-3
Abstract: PurposeOur purpose was to use deep learning for the automated detection of age-related macular degeneration (AMD) in spectral domain optical coherence tomography (SD-OCT).MethodsA total of 1112 cross-section SD-OCT images of patients with exudative AMD and… read more here.
Keywords: automated detection; learning; age related; related macular ... See more keywords
Automated detection of anomalies in cervix cells using image analysis and machine learning
Sign Up to like & getrecommendations! Published in 2018 at "Comparative Clinical Pathology"
DOI: 10.1007/s00580-018-2812-4
Abstract: Usage machine-based learning image cytometry to establish the diagnosis of cervix cancer using cellular morphology classification in comparison to the conventional cytological test. The study was divided into two phases consisting of 15 samples of… read more here.
Keywords: machine; image; machine learning; automated detection ... See more keywords
Efficient automated detection of mitotic cells from breast histological images using deep convolution neutral network with wavelet decomposed patches
Sign Up to like & getrecommendations! Published in 2019 at "Computers in biology and medicine"
DOI: 10.1016/j.compbiomed.2018.11.001
Abstract: In medical practice, the mitotic cell count from histological images acts as a proliferative marker for cancer diagnosis. Therefore, an accurate method for detecting mitotic cells in histological images is essential for cancer screening. Manual… read more here.
Keywords: mitotic cell; detection; automated detection; detection mitotic ... See more keywords
Novel automated PD detection system using aspirin pattern with EEG signals
Sign Up to like & getrecommendations! Published in 2021 at "Computers in biology and medicine"
DOI: 10.1016/j.compbiomed.2021.104841
Abstract: BACKGROUND AND OBJECTIVE Parkinson's disease (PD) is one of the most common diseases worldwide which reduces quality of life of patients and their family members. The electroencephalogram (EEG) signals coupled with various advanced machine-learning algorithms… read more here.
Keywords: eeg signals; automated detection; aspirin pattern;
Automated detection of hypertension using wavelet transform and nonlinear techniques with ballistocardiogram signals
Sign Up to like & getrecommendations! Published in 2021 at "Informatics in Medicine Unlocked"
DOI: 10.1016/j.imu.2021.100736
Abstract: Abstract Arterial hypertension (HT) is a common cardiovascular disease and, if not treated at an early stage, can lead to serious complications. It is difficult to precisely describe because it is a dynamic physiological state.… read more here.
Keywords: automated detection; wavelet transform; transform nonlinear; hypertension ... See more keywords
Smartwatch Algorithm for Automated Detection of Atrial Fibrillation.
Sign Up to like & getrecommendations! Published in 2018 at "Journal of the American College of Cardiology"
DOI: 10.1016/j.jacc.2018.03.003
Abstract: BACKGROUND The Kardia Band (KB) is a novel technology that enables patients to record a rhythm strip using an Apple Watch (Apple, Cupertino, California). The band is paired with an app providing automated detection of… read more here.
Keywords: atrial fibrillation; detection; automated detection; detection atrial ... See more keywords
Fully automated detection and segmentation of intracranial aneurysms in subarachnoid hemorrhage on CTA using deep learning
Sign Up to like & getrecommendations! Published in 2020 at "Scientific Reports"
DOI: 10.1038/s41598-020-78384-1
Abstract: In aneurysmal subarachnoid hemorrhage (aSAH), accurate diagnosis of aneurysm is essential for subsequent treatment to prevent rebleeding. However, aneurysm detection proves to be challenging and time-consuming. The purpose of this study was to develop and… read more here.
Keywords: automated detection; detection; subarachnoid hemorrhage; deep learning ... See more keywords