Literature DB >> 31267716

The advent of AI and deep learning in diagnostics and imaging: Machine learning systems have potential to improve diagnostics in healthcare and imaging systems in research.

Philip Hunter1.   

Abstract

Machine learning systems are increasingly applied in health care and the life sciences with great potential for cancer diagnostics and optical microscopy.
© 2019 The Author.

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Mesh：

Year:  2019        PMID： 31267716      PMCID： PMC6607001          DOI： 10.15252/embr.201948559

Source DB:  PubMed          Journal:  EMBO Rep        ISSN： 1469-221X            Impact factor:   8.807


  2 in total

1.  Deep learning massively accelerates super-resolution localization microscopy.

Authors:  Wei Ouyang; Andrey Aristov; Mickaël Lelek; Xian Hao; Christophe Zimmer
Journal:  Nat Biotechnol       Date:  2018-04-16       Impact factor: 54.908

2.  Deep learning enables cross-modality super-resolution in fluorescence microscopy.

Authors:  Hongda Wang; Yair Rivenson; Yiyin Jin; Zhensong Wei; Ronald Gao; Harun Günaydın; Laurent A Bentolila; Comert Kural; Aydogan Ozcan
Journal:  Nat Methods       Date:  2018-12-17       Impact factor: 28.547
  2 in total
  2 in total

1.  Deep-learning-assisted Fourier transform imaging spectroscopy for hyperspectral fluorescence imaging.

Authors:  Cory Juntunen; Isabel M Woller; Andrew R Abramczyk; Yongjin Sung
Journal:  Sci Rep       Date:  2022-02-15       Impact factor: 4.379

2.  Classifications of Neurodegenerative Disorders Using a Multiplex Blood Biomarkers-Based Machine Learning Model.

Authors:  Chin-Hsien Lin; Shu-I Chiu; Ta-Fu Chen; Jyh-Shing Roger Jang; Ming-Jang Chiu
Journal:  Int J Mol Sci       Date:  2020-09-21       Impact factor: 5.923
  2 in total

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