Literature DB >> 35136337

Artificial Intelligence: Review of Current and Future Applications in Medicine.

L Brannon Thomas1,2, Stephen M Mastorides1,2, Narayan A Viswanadhan1, Colleen E Jakey1,2, Andrew A Borkowski1,2.   

Abstract

BACKGROUND: The role of artificial intelligence (AI) in health care is expanding rapidly. Currently, there are at least 29 US Food and Drug Administration-approved AI health care devices that apply to numerous medical specialties and many more are in development. OBSERVATIONS: With increasing expectations for all health care sectors to deliver timely, fiscally-responsible, high-quality health care, AI has potential utility in numerous areas, such as image analysis, improved workflow and efficiency, public health, and epidemiology, to aid in processing large volumes of patient and medical data. In this review, we describe basic terminology, principles, and general AI applications relating to health care. We then discuss current and future applications for a variety of medical specialties. Finally, we discuss the future potential of AI along with the potential risks and limitations of current AI technology.
CONCLUSIONS: AI can improve diagnostic accuracy, increase patient safety, assist with patient triage, monitor disease progression, and assist with treatment decisions.
Copyright © 2021 Frontline Medical Communications Inc., Parsippany, NJ, USA.

Entities:  

Year:  2021        PMID: 35136337      PMCID: PMC8815615          DOI: 10.12788/fp.0174

Source DB:  PubMed          Journal:  Fed Pract        ISSN: 1078-4497


  107 in total

Review 1.  Deep neural networks in psychiatry.

Authors:  Daniel Durstewitz; Georgia Koppe; Andreas Meyer-Lindenberg
Journal:  Mol Psychiatry       Date:  2019-02-15       Impact factor: 15.992

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

Authors:  Varun Gulshan; Lily Peng; Marc Coram; Martin C Stumpe; Derek Wu; Arunachalam Narayanaswamy; Subhashini Venugopalan; Kasumi Widner; Tom Madams; Jorge Cuadros; Ramasamy Kim; Rajiv Raman; Philip C Nelson; Jessica L Mega; Dale R Webster
Journal:  JAMA       Date:  2016-12-13       Impact factor: 56.272

3.  Is artificial intelligence going to replace dermatologists?

Authors:  Faezeh Talebi-Liasi; Orit Markowitz
Journal:  Cutis       Date:  2020-01

4.  Artificial Intelligence in Ophthalmology in 2020: A Technology on the Cusp for Translation and Implementation.

Authors:  Dinesh Visva Gunasekeran; Tien Yin Wong
Journal:  Asia Pac J Ophthalmol (Phila)       Date:  2020 Mar-Apr

5.  Comparing the performance of artificial intelligence and conventional diagnosis criteria for detecting left ventricular hypertrophy using electrocardiography.

Authors:  Joon-Myoung Kwon; Ki-Hyun Jeon; Hyue Mee Kim; Min Jeong Kim; Sung Min Lim; Kyung-Hee Kim; Pil Sang Song; Jinsik Park; Rak Kyeong Choi; Byung-Hee Oh
Journal:  Europace       Date:  2020-03-01       Impact factor: 5.214

6.  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

7.  Using Administrative Data to Predict Suicide After Psychiatric Hospitalization in the Veterans Health Administration System.

Authors:  Ronald C Kessler; Mark S Bauer; Todd M Bishop; Olga V Demler; Steven K Dobscha; Sarah M Gildea; Joseph L Goulet; Elizabeth Karras; Julie Kreyenbuhl; Sara J Landes; Howard Liu; Alex R Luedtke; Patrick Mair; William H B McAuliffe; Matthew Nock; Maria Petukhova; Wilfred R Pigeon; Nancy A Sampson; Jordan W Smoller; Lauren M Weinstock; Robert M Bossarte
Journal:  Front Psychiatry       Date:  2020-05-06       Impact factor: 4.157

8.  A GIS-Based Artificial Neural Network Model for Spatial Distribution of Tuberculosis across the Continental United States.

Authors:  Abolfazl Mollalo; Liang Mao; Parisa Rashidi; Gregory E Glass
Journal:  Int J Environ Res Public Health       Date:  2019-01-08       Impact factor: 3.390

9.  International evaluation of an AI system for breast cancer screening.

Authors:  Scott Mayer McKinney; Marcin Sieniek; Varun Godbole; Jonathan Godwin; Natasha Antropova; Hutan Ashrafian; Trevor Back; Mary Chesus; Greg S Corrado; Ara Darzi; Mozziyar Etemadi; Florencia Garcia-Vicente; Fiona J Gilbert; Mark Halling-Brown; Demis Hassabis; Sunny Jansen; Alan Karthikesalingam; Christopher J Kelly; Dominic King; Joseph R Ledsam; David Melnick; Hormuz Mostofi; Lily Peng; Joshua Jay Reicher; Bernardino Romera-Paredes; Richard Sidebottom; Mustafa Suleyman; Daniel Tse; Kenneth C Young; Jeffrey De Fauw; Shravya Shetty
Journal:  Nature       Date:  2020-01-01       Impact factor: 49.962

10.  Classification and mutation prediction from non-small cell lung cancer histopathology images using deep learning.

Authors:  Nicolas Coudray; Paolo Santiago Ocampo; Theodore Sakellaropoulos; Navneet Narula; Matija Snuderl; David Fenyö; Andre L Moreira; Narges Razavian; Aristotelis Tsirigos
Journal:  Nat Med       Date:  2018-09-17       Impact factor: 53.440

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.