Cargando…

End-to-end deep learning radiomics: development and validation of a novel attention-based aggregate convolutional neural network to distinguish breast diffuse large B-cell lymphoma from breast invasive ductal carcinoma

BACKGROUND: Apart from invasive pathological examination, there is no effective method to differentiate breast diffuse large B-cell lymphoma (DLBCL) from breast invasive ductal carcinoma (IDC). In this study, we aimed to develop and validate an effective deep learning radiomics model to discriminate...

Descripción completa

Detalles Bibliográficos
Autores principales:	Chen, Wen, Liu, Fei, Wang, Rui, Qi, Ming, Zhang, Jianping, Liu, Xiaosheng, Song, Shaoli
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	AME Publishing Company 2023
Materias:	Original Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10585556/ https://www.ncbi.nlm.nih.gov/pubmed/37869296 http://dx.doi.org/10.21037/qims-22-1333

Ejemplares similares

Ability of (18)F-FDG PET/CT Radiomic Features to Distinguish Breast Carcinoma from Breast Lymphoma
por: Ou, Xuejin, et al.
Publicado: (2019)

GPS Trajectory Completion Using End-to-End Bidirectional Convolutional Recurrent Encoder-Decoder Architecture with Attention Mechanism
por: Nawaz, Asif, et al.
Publicado: (2020)

An ultrasound-based radiomics model to distinguish between sclerosing adenosis and invasive ductal carcinoma
por: Huang, Qun, et al.
Publicado: (2023)

A Novel End-To-End Fault Diagnosis Approach for Rolling Bearings by Integrating Wavelet Packet Transform into Convolutional Neural Network Structures
por: Xiong, Shoucong, et al.
Publicado: (2020)

An end-to-end convolutional neural network for automated failure localisation and characterisation of 3D interconnects
por: Paulachan, Priya, et al.
Publicado: (2023)

Infiltrating Ductal Carcinoma of the Breast Associated with Primary Breast Lymphoma
por: Arlen, Myron, et al.
Publicado: (2011)

A Radiomics Nomogram for Distinguishing Benign From Malignant Round-Like Breast Tumors
por: Wang, Lanyun, et al.
Publicado: (2022)

An Invasive Ductal Carcinomas Breast Cancer Grade Classification Using an Ensemble of Convolutional Neural Networks
por: Kumaraswamy, Eelandula, et al.
Publicado: (2023)

Prognostic value of ductal carcinoma in situ component in invasive ductal carcinoma of the breast: a Surveillance, Epidemiology, and End Results database analysis
por: Wu, San-Gang, et al.
Publicado: (2018)

Triexponential Diffusion Analysis of Diffusion-weighted Imaging for Breast Ductal Carcinoma in Situ and Invasive Ductal Carcinoma
por: Ohno, Masako, et al.
Publicado: (2021)

Periodic-net: an end-to-end data driven framework for diffuse optical imaging of breast cancer from noisy boundary data
por: Murad, Nazish, et al.
Publicado: (2023)

End-to-end speech emotion recognition using a novel context-stacking dilated convolution neural network
por: Tang, Duowei, et al.
Publicado: (2021)

Apparent Diffusion Coefficient-Based Convolutional Neural Network Model Can Be Better Than Sole Diffusion-Weighted Magnetic Resonance Imaging to Improve the Differentiation of Invasive Breast Cancer From Breast Ductal Carcinoma In Situ
por: Yin, Haolin, et al.
Publicado: (2022)

Machine Learning Algorithm for Distinguishing Ductal Carcinoma In Situ from Invasive Breast Cancer
por: Vy, Vu Pham Thao, et al.
Publicado: (2022)

An End-to-End Lane Detection Model with Attention and Residual Block
por: Wang, Bo, et al.
Publicado: (2022)

End-to-End Point Cloud Completion Network with Attention Mechanism
por: Li, Yaqin, et al.
Publicado: (2022)

Convolutional neural network for breast cancer diagnosis using diffuse optical tomography
por: Xu, Qiwen, et al.
Publicado: (2019)

End-to-End Deep Convolutional Recurrent Models for Noise Robust Waveform Speech Enhancement
por: Ullah, Rizwan, et al.
Publicado: (2022)

COmic: convolutional kernel networks for interpretable end-to-end learning on (multi-)omics data
por: Ditz, Jonas C, et al.
Publicado: (2023)

Immunotherapy for triple negative breast cancer: the end of the beginning or the beginning of the end?
por: Wojtukiewicz, Marek Z., et al.
Publicado: (2022)

Convolutional Neural Network for the Detection of End-Diastole and End-Systole Frames in Free-Breathing Cardiac Magnetic Resonance Imaging
por: Yang, Fan, et al.
Publicado: (2017)

Optimization of End-to-End Convolutional Neural Networks for Analysis of Out-of-Hospital Cardiac Arrest Rhythms during Cardiopulmonary Resuscitation
por: Jekova, Irena, et al.
Publicado: (2021)

End-to-End Implementation of a Convolutional Neural Network on a 3D-Integrated Image Sensor with Macropixel Array
por: Lepecq, Maria, et al.
Publicado: (2023)

An End-to-End Multi-Channel Convolutional Bi-LSTM Network for Automatic Sleep Stage Detection
por: Toma, Tabassum Islam, et al.
Publicado: (2023)

A Multi-Task Framework for Facial Attributes Classification through End-to-End Face Parsing and Deep Convolutional Neural Networks
por: Khan, Khalil, et al.
Publicado: (2020)

End-to-End Deep Graph Convolutional Neural Network Approach for Intentional Islanding in Power Systems Considering Load-Generation Balance
por: Sun, Zhonglin, et al.
Publicado: (2021)

Primary chemotherapy in breast cancer: The beginning of the end or the end of the beginning for the surgical oncologist?
por: Heys, Steven D, et al.
Publicado: (2003)

Preoperative ultrasound radiomics analysis for expression of multiple molecular biomarkers in mass type of breast ductal carcinoma in situ
por: Wu, Linyong, et al.
Publicado: (2021)

Machine learning based on clinico-biological features integrated (18)F-FDG PET/CT radiomics for distinguishing squamous cell carcinoma from adenocarcinoma of lung
por: Ren, Caiyue, et al.
Publicado: (2020)

Potential of the Non-Contrast-Enhanced Chest CT Radiomics to Distinguish Molecular Subtypes of Breast Cancer: A Retrospective Study
por: Wang, Fei, et al.
Publicado: (2022)

Rapid Diagnosis of Ductal Carcinoma In Situ and Breast Cancer Based on Raman Spectroscopy of Serum Combined with Convolutional Neural Network
por: Wang, Xianglei, et al.
Publicado: (2023)

Primary breast diffuse large B cell lymphoma
por: Guo, Mengni, et al.
Publicado: (2022)

End-to-End Depression Recognition Based on a One-Dimensional Convolution Neural Network Model Using Two-Lead ECG Signal
por: Zang, Xiaohan, et al.
Publicado: (2022)

End-to-End Convolutional Neural Network Model to Detect and Localize Myocardial Infarction Using 12-Lead ECG Images without Preprocessing
por: Uchiyama, Ryunosuke, et al.
Publicado: (2022)

End-to-End One-Shot Path-Planning Algorithm for an Autonomous Vehicle Based on a Convolutional Neural Network Considering Traversability Cost
por: Bian, Tongfei, et al.
Publicado: (2022)

“Omic” landscapes of breast cancer - the end of the beginning
por: Caldas, Carlos
Publicado: (2010)

An end-to-end heterogeneous graph attention network for Mycobacterium tuberculosis drug-resistance prediction
por: Yang, Yang, et al.
Publicado: (2021)

Technical Note: Development of 3D‐printed breast phantoms for end‐to‐end testing of whole breast volumetric arc radiotherapy
por: Delombaerde, Laurence, et al.
Publicado: (2020)

Diffusion MRI tractography of the human heart In Vivo at end-diastole and end-systole
por: Mekkaoui, Choukri, et al.
Publicado: (2012)

Direct pixel to pixel principal strain mapping from tagging MRI using end to end deep convolutional neural network (DeepStrain)
por: Abd-Elmoniem, Khaled Z., et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_qu1h72h23sjobr1eiugasnetqr