Literature DB >> 29474917

Learning from Everyday Images Enables Expert-like Diagnosis of Retinal Diseases.

Ladislav Rampasek1, Anna Goldenberg2.   

Abstract

Kermany et al. report an application of a neural network trained on millions of everyday images to a database of thousands of retinal tomography images that they gathered and expert labeled, resulting in a rapid and accurate diagnosis of retinal diseases.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Mesh：

Year:  2018        PMID： 29474917     DOI： 10.1016/j.cell.2018.02.013

Source DB:  PubMed          Journal:  Cell        ISSN： 0092-8674            Impact factor:   41.582


  9 in total

Review 1.  High-performance medicine: the convergence of human and artificial intelligence.

Authors:  Eric J Topol
Journal:  Nat Med       Date:  2019-01-07       Impact factor: 53.440

2.  Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning.

Authors:  Mohammad Sadegh Norouzzadeh; Anh Nguyen; Margaret Kosmala; Alexandra Swanson; Meredith S Palmer; Craig Packer; Jeff Clune
Journal:  Proc Natl Acad Sci U S A       Date:  2018-06-05       Impact factor: 11.205

3.  QC-Automator: Deep Learning-Based Automated Quality Control for Diffusion MR Images.

Authors:  Zahra Riahi Samani; Jacob Antony Alappatt; Drew Parker; Abdol Aziz Ould Ismail; Ragini Verma
Journal:  Front Neurosci       Date:  2020-01-22       Impact factor: 4.677

4.  Quantitative analysis of functional filtering bleb size using Mask R-CNN.

Authors:  Tao Wang; Lei Zhong; Jing Yuan; Ting Wang; Shiyi Yin; Yi Sun; Xing Liu; Xun Liu; Shiqi Ling
Journal:  Ann Transl Med       Date:  2020-06

5.  A deep-learning based multimodal system for Covid-19 diagnosis using breathing sounds and chest X-ray images.

Authors:  Unais Sait; Gokul Lal K V; Sanjana Shivakumar; Tarun Kumar; Rahul Bhaumik; Sunny Prajapati; Kriti Bhalla; Anaghaa Chakrapani
Journal:  Appl Soft Comput       Date:  2021-05-26       Impact factor: 6.725

6.  The Combination of Adaptive Convolutional Neural Network and Bag of Visual Words in Automatic Diagnosis of Third Molar Complications on Dental X-Ray Images.

Authors:  Vo Truong Nhu Ngoc; Agwu Chinedu Agwu; Le Hoang Son; Tran Manh Tuan; Cu Nguyen Giap; Mai Thi Giang Thanh; Hoang Bao Duy; Tran Thi Ngan
Journal:  Diagnostics (Basel)       Date:  2020-04-09

7.  Identifying Smoking Environments From Images of Daily Life With Deep Learning.

Authors:  Matthew M Engelhard; Jason A Oliver; Ricardo Henao; Matt Hallyburton; Lawrence E Carin; Cynthia Conklin; F Joseph McClernon
Journal:  JAMA Netw Open       Date:  2019-08-02

8.  Preoperative identification of microvascular invasion in hepatocellular carcinoma by XGBoost and deep learning.

Authors:  Yi-Quan Jiang; Su-E Cao; Shilei Cao; Jian-Ning Chen; Guo-Ying Wang; Wen-Qi Shi; Yi-Nan Deng; Na Cheng; Kai Ma; Kai-Ning Zeng; Xi-Jing Yan; Hao-Zhen Yang; Wen-Jing Huan; Wei-Min Tang; Yefeng Zheng; Chun-Kui Shao; Jin Wang; Yang Yang; Gui-Hua Chen
Journal:  J Cancer Res Clin Oncol       Date:  2020-08-27       Impact factor: 4.553

Review 9.  Machine Learning in Healthcare.

Authors:  Hafsa Habehh; Suril Gohel
Journal:  Curr Genomics       Date:  2021-12-16       Impact factor: 2.689
  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.