Literature DB >> 31699402

AI-augmented multidisciplinary teams: hype or hope?

Antonio Di Ieva1.   

Abstract

Entities:  

Mesh：

Year:  2019        PMID： 31699402     DOI： 10.1016/S0140-6736(19)32626-1

Source DB:  PubMed          Journal:  Lancet        ISSN： 0140-6736            Impact factor:   79.321


× No keyword cloud information.
  6 in total

1.  Changing Health-Related Behaviors 6: Analysis, Interpretation, and Application of Big Data.

Authors:  Randy Giffen; Donald Bryant
Journal:  Methods Mol Biol       Date:  2021

2.  Application of deep learning for automatic segmentation of brain tumors on magnetic resonance imaging: a heuristic approach in the clinical scenario.

Authors:  Antonio Di Ieva; Carlo Russo; Sidong Liu; Anne Jian; Michael Y Bai; Yi Qian; John S Magnussen
Journal:  Neuroradiology       Date:  2021-01-26       Impact factor: 2.804

Review 3.  Great future or greedy venture: Precision medicine needs philosophy.

Authors:  Fei Jiao; Ruoyu Guo; Jacques S Beckmann; Zhonghai Yan; Yun Yang; Jinxia Hu; Xin Wang; Shuyang Xie
Journal:  Health Sci Rep       Date:  2021-09-14

4.  Politics by Automatic Means? A Critique of Artificial Intelligence Ethics at Work.

Authors:  Matthew Cole; Callum Cant; Funda Ustek Spilda; Mark Graham
Journal:  Front Artif Intell       Date:  2022-07-15

Review 5.  Applications of machine learning methods in kidney disease: hope or hype?

Authors:  Lili Chan; Akhil Vaid; Girish N Nadkarni
Journal:  Curr Opin Nephrol Hypertens       Date:  2020-05       Impact factor: 3.416

Review 6.  Machine Learning for Cardiovascular Outcomes From Wearable Data: Systematic Review From a Technology Readiness Level Point of View.

Authors:  Arman Naseri Jahfari; David Tax; Marcel Reinders; Ivo van der Bilt
Journal:  JMIR Med Inform       Date:  2022-01-19
  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.