Articles with "learning based" as a keyword



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Assessment of Machine Learning–Based Medical Directives to Expedite Care in Pediatric Emergency Medicine

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Published in 2022 at "JAMA Network Open"

DOI: 10.1001/jamanetworkopen.2022.2599

Abstract: Key Points Question Can machine learning–based medical directives (MLMDs) be used to autonomously order testing at triage for common pediatric presentations in the emergency department? Findings This decision analytical model analyzing 77 219 presentations of children… read more here.

Keywords: emergency; machine learning; medical directives; based medical ... See more keywords
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Development and Validation of a Deep Learning–Based Synthetic Bone-Suppressed Model for Pulmonary Nodule Detection in Chest Radiographs

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Published in 2023 at "JAMA Network Open"

DOI: 10.1001/jamanetworkopen.2022.53820

Abstract: Key Points Question Can a deep learning–based synthetic bone-suppressed (DLBS) model additionally improve the detection of pulmonary nodules on chest radiographs? Findings In this decision analytical modeling study of 1449 patients, the DLBS model was… read more here.

Keywords: detection; chest radiographs; deep learning; model ... See more keywords
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A sensitivity analysis of probability maps in deep‐learning‐based anatomical segmentation

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Published in 2021 at "Journal of Applied Clinical Medical Physics"

DOI: 10.1002/acm2.13331

Abstract: Abstract Purpose Deep‐learning‐based segmentation models implicitly learn to predict the presence of a structure based on its overall prominence in the training dataset. This phenomenon is observed and accounted for in deep‐learning applications such as… read more here.

Keywords: segmentation; anatomical segmentation; deep learning; learning based ... See more keywords
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Dosimetric assessment of patient dose calculation on a deep learning‐based synthesized computed tomography image for adaptive radiotherapy

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Published in 2022 at "Journal of Applied Clinical Medical Physics"

DOI: 10.1002/acm2.13595

Abstract: Abstract Purpose Dose computation using cone beam computed tomography (CBCT) images is inaccurate for the purpose of adaptive treatment planning. The main goal of this study is to assess the dosimetric accuracy of synthetic computed… read more here.

Keywords: computed tomography; deep learning; learning based; image ... See more keywords
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Advanced Deep Learning‐Based 3D Microstructural Characterization of Multiphase Metal Matrix Composites

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Published in 2020 at "Advanced Engineering Materials"

DOI: 10.1002/adem.201901197

Abstract: The quantitative analysis of microstructural features is a key to understanding the micromechanical behavior of metal matrix composites (MMCs), which is a premise for their use in practice. Herein, a 3D microstructural characterization of a… read more here.

Keywords: microstructural characterization; advanced deep; deep learning; matrix composites ... See more keywords
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Bridging the gap: Development of an experiential learning–based health disparities curriculum

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Published in 2022 at "AEM Education and Training"

DOI: 10.1002/aet2.10820

Abstract: The increasing number of vulnerable populations served by the emergency department (ED) calls for developing and implementing curricula aimed at training residents to deliver quality care for the most marginalized groups. read more here.

Keywords: experiential learning; development experiential; based health; bridging gap ... See more keywords
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Development and evaluation of a colorectal cancer screening method using machine learning‐based gut microbiota analysis

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Published in 2022 at "Cancer Medicine"

DOI: 10.1002/cam4.4671

Abstract: Accumulating evidence indicates that alterations of gut microbiota are associated with colorectal cancer (CRC). Therefore, the use of gut microbiota for the diagnosis of CRC has received attention. Recently, several studies have been conducted to… read more here.

Keywords: learning based; machine learning; cancer; gut microbiota ... See more keywords
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Expected and observed in‐hospital mortality in heart failure patients before and during the COVID‐19 pandemic: Introduction of the machine learning‐based standardized mortality ratio at Helios hospitals

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Published in 2021 at "Clinical Cardiology"

DOI: 10.1002/clc.23762

Abstract: Reduced hospital admission rates for heart failure (HF) and evidence of increased in‐hospital mortality were reported during the COVID‐19 pandemic. The aim of this study was to apply a machine learning (ML)‐based mortality prediction model… read more here.

Keywords: learning based; machine learning; heart failure; mortality ... See more keywords
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Direct cortical thickness estimation using deep learning‐based anatomy segmentation and cortex parcellation

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Published in 2020 at "Human Brain Mapping"

DOI: 10.1002/hbm.25159

Abstract: Accurate and reliable measures of cortical thickness from magnetic resonance imaging are an important biomarker to study neurodegenerative and neurological disorders. Diffeomorphic registration‐based cortical thickness (DiReCT) is a known technique to derive such measures from… read more here.

Keywords: segmentation; anatomy; deep learning; learning based ... See more keywords
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An integrated deep learning‐based model of spatial cells that combines self‐motion with sensory information

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Published in 2022 at "Hippocampus"

DOI: 10.1002/hipo.23461

Abstract: A special class of neurons in the hippocampal formation broadly known as the spatial cells, whose subcategories include place cells, grid cells, and head direction cells, are considered to be the building blocks of the… read more here.

Keywords: deep learning; model; direction; spatial cells ... See more keywords
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Deep learning and machine learning‐based early survival predictions of glioblastoma patients using pre‐operative three‐dimensional brain magnetic resonance imaging modalities

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Published in 2022 at "International Journal of Imaging Systems and Technology"

DOI: 10.1002/ima.22804

Abstract: To propose and implement an automated machine learning (ML) based methodology to predict the overall survival of glioblastoma multiforme (GBM) patients. In the proposed methodology, we used deep learning (DL) based 3D U‐shaped Convolutional Neural… read more here.

Keywords: methodology; machine learning; feature; brain ... See more keywords