Literature DB >> 33420381

Deep learning-enabled medical computer vision.

Andre Esteva1, Katherine Chou2, Serena Yeung3, Nikhil Naik4, Ali Madani4, Ali Mottaghi3, Yun Liu2, Eric Topol5, Jeff Dean2, Richard Socher4.   

Abstract

A decade of unprecedented progress in artificial intelligence (AI) has demonstrated the potential for many fields-including medicine-to benefit from the insights that AI techniques can extract from data. Here we survey recent progress in the development of modern computer vision techniques-powered by deep learning-for medical applications, focusing on medical imaging, medical video, and clinical deployment. We start by briefly summarizing a decade of progress in convolutional neural networks, including the vision tasks they enable, in the context of healthcare. Next, we discuss several example medical imaging applications that stand to benefit-including cardiology, pathology, dermatology, ophthalmology-and propose new avenues for continued work. We then expand into general medical video, highlighting ways in which clinical workflows can integrate computer vision to enhance care. Finally, we discuss the challenges and hurdles required for real-world clinical deployment of these technologies.

Entities:  

Year:  2021        PMID: 33420381     DOI: 10.1038/s41746-020-00376-2

Source DB:  PubMed          Journal:  NPJ Digit Med        ISSN: 2398-6352


  86 in total

Review 1.  A contemporary review of machine learning in otolaryngology-head and neck surgery.

Authors:  Matthew G Crowson; Jonathan Ranisau; Antoine Eskander; Aaron Babier; Bin Xu; Russel R Kahmke; Joseph M Chen; Timothy C Y Chan
Journal:  Laryngoscope       Date:  2019-02-01       Impact factor: 3.325

2.  The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database.

Authors:  Stan Benjamens; Pranavsingh Dhunnoo; Bertalan Meskó
Journal:  NPJ Digit Med       Date:  2020-09-11

3.  An augmented reality microscope with real-time artificial intelligence integration for cancer diagnosis.

Authors:  Po-Hsuan Cameron Chen; Krishna Gadepalli; Robert MacDonald; Yun Liu; Shiro Kadowaki; Kunal Nagpal; Timo Kohlberger; Jeffrey Dean; Greg S Corrado; Jason D Hipp; Craig H Mermel; Martin C Stumpe
Journal:  Nat Med       Date:  2019-08-12       Impact factor: 53.440

Review 4.  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

Review 5.  A guide to deep learning in healthcare.

Authors:  Andre Esteva; Alexandre Robicquet; Bharath Ramsundar; Volodymyr Kuleshov; Mark DePristo; Katherine Chou; Claire Cui; Greg Corrado; Sebastian Thrun; Jeff Dean
Journal:  Nat Med       Date:  2019-01-07       Impact factor: 53.440

6.  A computer vision system for deep learning-based detection of patient mobilization activities in the ICU.

Authors:  Serena Yeung; Francesca Rinaldo; Jeffrey Jopling; Bingbin Liu; Rishab Mehra; N Lance Downing; Michelle Guo; Gabriel M Bianconi; Alexandre Alahi; Julia Lee; Brandi Campbell; Kayla Deru; William Beninati; Li Fei-Fei; Arnold Milstein
Journal:  NPJ Digit Med       Date:  2019-03-01

7.  Building an Otoscopic screening prototype tool using deep learning.

Authors:  Devon Livingstone; Aron S Talai; Justin Chau; Nils D Forkert
Journal:  J Otolaryngol Head Neck Surg       Date:  2019-11-26

8.  Automatic detection of hand hygiene using computer vision technology.

Authors:  Amit Singh; Albert Haque; Alexandre Alahi; Serena Yeung; Michelle Guo; Jill R Glassman; William Beninati; Terry Platchek; Li Fei-Fei; Arnold Milstein
Journal:  J Am Med Inform Assoc       Date:  2020-08-01       Impact factor: 4.497

9.  Video-based AI for beat-to-beat assessment of cardiac function.

Authors:  David Ouyang; Bryan He; Amirata Ghorbani; Neal Yuan; Joseph Ebinger; Curtis P Langlotz; Paul A Heidenreich; Robert A Harrington; David H Liang; Euan A Ashley; James Y Zou
Journal:  Nature       Date:  2020-03-25       Impact factor: 49.962

10.  Mapping of Crowdsourcing in Health: Systematic Review.

Authors:  Perrine Créquit; Ghizlène Mansouri; Mehdi Benchoufi; Alexandre Vivot; Philippe Ravaud
Journal:  J Med Internet Res       Date:  2018-05-15       Impact factor: 5.428

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  36 in total

1.  The Cases for and against Artificial Intelligence in the Medical School Curriculum.

Authors:  Brandon Ngo; Diep Nguyen; Eric vanSonnenberg
Journal:  Radiol Artif Intell       Date:  2022-08-17

2.  Development of deep learning-assisted overscan decision algorithm in low-dose chest CT: Application to lung cancer screening in Korean National CT accreditation program.

Authors:  Sihwan Kim; Woo Kyoung Jeong; Jin Hwa Choi; Jong Hyo Kim; Minsoo Chun
Journal:  PLoS One       Date:  2022-09-29       Impact factor: 3.752

Review 3.  Multimodal biomedical AI.

Authors:  Julián N Acosta; Guido J Falcone; Pranav Rajpurkar; Eric J Topol
Journal:  Nat Med       Date:  2022-09-15       Impact factor: 87.241

4.  Security Evaluation of Financial and Insurance and Ruin Probability Analysis Integrating Deep Learning Models.

Authors:  Yang Yang
Journal:  Comput Intell Neurosci       Date:  2022-06-08

5.  DeepLensNet: Deep Learning Automated Diagnosis and Quantitative Classification of Cataract Type and Severity.

Authors:  Tiarnan D L Keenan; Qingyu Chen; Elvira Agrón; Yih-Chung Tham; Jocelyn Hui Lin Goh; Xiaofeng Lei; Yi Pin Ng; Yong Liu; Xinxing Xu; Ching-Yu Cheng; Mukharram M Bikbov; Jost B Jonas; Sanjeeb Bhandari; Geoffrey K Broadhead; Marcus H Colyer; Jonathan Corsini; Chantal Cousineau-Krieger; William Gensheimer; David Grasic; Tania Lamba; M Teresa Magone; Michele Maiberger; Arnold Oshinsky; Boonkit Purt; Soo Y Shin; Alisa T Thavikulwat; Zhiyong Lu; Emily Y Chew
Journal:  Ophthalmology       Date:  2022-01-03       Impact factor: 14.277

Review 6.  Artificial intelligence-enabled decision support in nephrology.

Authors:  Tyler J Loftus; Benjamin Shickel; Tezcan Ozrazgat-Baslanti; Yuanfang Ren; Benjamin S Glicksberg; Jie Cao; Karandeep Singh; Lili Chan; Girish N Nadkarni; Azra Bihorac
Journal:  Nat Rev Nephrol       Date:  2022-04-22       Impact factor: 42.439

7.  Session interest model for CTR prediction based on self-attention mechanism.

Authors:  Qianqian Wang; Fang'ai Liu; Xiaohui Zhao; Qiaoqiao Tan
Journal:  Sci Rep       Date:  2022-01-07       Impact factor: 4.379

8.  Assessment of the effect of a comprehensive chest radiograph deep learning model on radiologist reports and patient outcomes: a real-world observational study.

Authors:  Catherine M Jones; Luke Danaher; Michael R Milne; Cyril Tang; Jarrel Seah; Luke Oakden-Rayner; Andrew Johnson; Quinlan D Buchlak; Nazanin Esmaili
Journal:  BMJ Open       Date:  2021-12-20       Impact factor: 2.692

9.  Evaluating Deep Neural Network Architectures with Transfer Learning for Pneumonitis Diagnosis.

Authors:  Surya Krishnamurthy; Kathiravan Srinivasan; Saeed Mian Qaisar; P M Durai Raj Vincent; Chuan-Yu Chang
Journal:  Comput Math Methods Med       Date:  2021-09-12       Impact factor: 2.238

10.  Improving effectiveness of different deep learning-based models for detecting COVID-19 from computed tomography (CT) images.

Authors:  Erdi Acar; Engin Şahin; İhsan Yılmaz
Journal:  Neural Comput Appl       Date:  2021-07-29       Impact factor: 5.102

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