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   Articles with "deep learning" as a keyword



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Performance of a Deep Learning Model vs Human Reviewers in Grading Endoscopic Disease Severity of Patients With Ulcerative Colitis

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recommendations! Published in 2019 at "JAMA Network Open"

DOI: 10.1001/jamanetworkopen.2019.3963

Abstract: Key Points Question What is the agreement of automatically determined endoscopic severity of ulcerative colitis using deep learning models compared with expert human reviewers? Findings In this diagnostic study including colonoscopy data from 3082 adults,… read more here.

Keywords: severity; ulcerative colitis; human reviewers; deep learning ... See more keywords
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Deep Learning–Assisted Diagnosis of Cerebral Aneurysms Using the HeadXNet Model

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recommendations! Published in 2019 at "JAMA Network Open"

DOI: 10.1001/jamanetworkopen.2019.5600

Abstract: Key Points Question How does augmentation with a deep learning segmentation model influence the performance of clinicians in identifying intracranial aneurysms from computed tomographic angiography examinations? Findings In this diagnostic study of intracranial aneurysms, a… read more here.

Keywords: learning; intracranial aneurysms; deep learning; assisted diagnosis ... See more keywords
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Development and Validation of a Deep Learning Model to Predict the Occurrence and Severity of Retinopathy of Prematurity.

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recommendations! Published in 2022 at "JAMA network open"

DOI: 10.1001/jamanetworkopen.2022.17447

Abstract: Importance Retinopathy of prematurity (ROP) is the leading cause of childhood blindness worldwide. Prediction of ROP before onset holds great promise for reducing the risk of blindness. Objective To develop and validate a deep learning… read more here.

Keywords: rop; validation; severity; deep learning ... 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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recommendations! 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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Development and Validation of a Joint Attention–Based Deep Learning System for Detection and Symptom Severity Assessment of Autism Spectrum Disorder

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recommendations! Published in 2023 at "JAMA Network Open"

DOI: 10.1001/jamanetworkopen.2023.15174

Abstract: Key Points Question Can joint attention be quantified for detecting autism spectrum disorder (ASD) and assessing ASD symptom severities? Findings In this diagnostic study of 45 children with ASD and 50 with typical development, a… read more here.

Keywords: development; joint attention; symptom severity; deep learning ... See more keywords
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Quantifying the Association Between Psychotherapy Content and Clinical Outcomes Using Deep Learning.

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recommendations! Published in 2019 at "JAMA psychiatry"

DOI: 10.1001/jamapsychiatry.2019.2664

Abstract: Importance Compared with the treatment of physical conditions, the quality of care of mental health disorders remains poor and the rate of improvement in treatment is slow, a primary reason being the lack of objective… read more here.

Keywords: improvement; clinical outcomes; cbt; treatment ... See more keywords
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Development and Validation of Image-Based Deep Learning Models to Predict Surgical Complexity and Complications in Abdominal Wall Reconstruction.

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recommendations! Published in 2021 at "JAMA surgery"

DOI: 10.1001/jamasurg.2021.3012

Abstract: Importance Image-based deep learning models (DLMs) have been used in other disciplines, but this method has yet to be used to predict surgical outcomes. Objective To apply image-based deep learning to predict complexity, defined as… read more here.

Keywords: image based; complexity; surgical complexity; deep learning ... See more keywords
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A sensitivity analysis of probability maps in deep‐learning‐based anatomical segmentation

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recommendations! 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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Deep learning‐based convolutional neural network for intramodality brain MRI synthesis

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

DOI: 10.1002/acm2.13530

Abstract: Abstract Purpose The existence of multicontrast magnetic resonance (MR) images increases the level of clinical information available for the diagnosis and treatment of brain cancer patients. However, acquiring the complete set of multicontrast MR images… read more here.

Keywords: neural network; brain mri; brain; convolutional neural ... 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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recommendations! 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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Deep learning for emergency ascites diagnosis using ultrasonography images

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

DOI: 10.1002/acm2.13695

Abstract: Abstract Purpose The detection of abdominal free fluid or hemoperitoneum can provide critical information for clinical diagnosis and treatment, particularly in emergencies. This study investigates the use of deep learning (DL) for identifying peritoneal free… read more here.

Keywords: emergency; ascites diagnosis; deep learning; ascites ascites ... See more keywords