Automatic anatomical classification of esophagogastroduodenoscopy images using deep convolutional neural networks.

about

Automatic anatomical classification of esophagogastroduodenoscopy images using deep convolutional neural networks.

Item

http://www.wikidata.org/entity/Q55075465

description

2018 nî lūn-bûn

@nan

2018年の論文

@ja

2018年学术文章

@wuu

2018年学术文章

@zh-cn

2018年学术文章

@zh-hans

2018年学术文章

@zh-my

2018年学术文章

@zh-sg

2018年學術文章

@yue

2018年學術文章

@zh

2018年學術文章

@zh-hant

name

Automatic anatomical classific ...... convolutional neural networks.

@en

Automatic anatomical classific ...... convolutional neural networks.

@nl

type

Item

label

Automatic anatomical classific ...... convolutional neural networks.

@en

Automatic anatomical classific ...... convolutional neural networks.

@nl

prefLabel

Automatic anatomical classific ...... convolutional neural networks.

@en

Automatic anatomical classific ...... convolutional neural networks.

@nl

P1476

Automatic anatomical classific ...... convolutional neural networks.

@en

P2093

Hirotoshi Takiyama

http://www.w3.org/2001/XMLSchema#string

Mitsuhiro Fujishiro

http://www.w3.org/2001/XMLSchema#string

Motoi Miura

http://www.w3.org/2001/XMLSchema#string

Soichiro Ishihara

http://www.w3.org/2001/XMLSchema#string

Tomohiro Tada

http://www.w3.org/2001/XMLSchema#string

Tsuyoshi Ozawa

http://www.w3.org/2001/XMLSchema#string

P2860

Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs

Dermatologist-level classification of skin cancer with deep neural networks

Big Data and machine learning in radiation oncology: State of the art and future prospects.

Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent.

Deep Learning for Fully-Automated Localization and Segmentation of Rectal Cancer on Multiparametric MR

Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning

Quality indicators for EGD.

Ultra-high definition (8K UHD) endoscope: our first clinical success.

Quantitative analysis of patients with celiac disease by video capsule endoscopy: A deep learning method.

Digital Mapping of the Urinary Bladder: Potential for Standardized Cystoscopy Reports.

P304

7497

http://www.w3.org/2001/XMLSchema#string

P31

scholarly article

P356

10.1038/S41598-018-25842-6

http://www.w3.org/2001/XMLSchema#string

P407

English

P433

http://www.w3.org/2001/XMLSchema#string

P478

http://www.w3.org/2001/XMLSchema#string

P50

Satoki Shichijo

Shuhei Nomura

P577

2018-05-14T00:00:00Z

http://www.w3.org/2001/XMLSchema#dateTime

P698

29760397

http://www.w3.org/2001/XMLSchema#string

P921

convolutional neural network

automation

deep learning

P932

5951793

http://www.w3.org/2001/XMLSchema#string