Literature DB >> 32402150

The utility of artificial intelligence in the assessment of prostate pathology.

Lars Egevad1,2, Peter Ström3, Kimmo Kartasalo4, Henrik Olsson3, Hemamali Samaratunga5,6, Brett Delahunt7, Martin Eklund3.   

Abstract

Mesh：

Year:  2020        PMID： 32402150     DOI： 10.1111/his.14060

Source DB:  PubMed          Journal:  Histopathology        ISSN： 0309-0167            Impact factor:   5.087


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  4 in total

1.  Detection of perineural invasion in prostate needle biopsies with deep neural networks.

Authors:  Kimmo Kartasalo; Peter Ström; Pekka Ruusuvuori; Hemamali Samaratunga; Brett Delahunt; Toyonori Tsuzuki; Martin Eklund; Lars Egevad
Journal:  Virchows Arch       Date:  2022-04-21       Impact factor: 4.535

2.  Development and Validation of an Artificial Intelligence-Powered Platform for Prostate Cancer Grading and Quantification.

Authors:  Wei Huang; Ramandeep Randhawa; Parag Jain; Kenneth A Iczkowski; Rong Hu; Samuel Hubbard; Jens Eickhoff; Hirak Basu; Rajat Roy
Journal:  JAMA Netw Open       Date:  2021-11-01

3.  Prostate cancer grading, time to go back to the future.

Authors:  Lars Egevad; Brett Delahunt; David G Bostwick; Liang Cheng; Andrew J Evans; Troy Gianduzzo; Markus Graefen; Jonas Hugosson; James G Kench; Katia R M Leite; Jon Oxley; Guido Sauter; John R Srigley; Pär Stattin; Toyonori Tsuzuki; John Yaxley; Hemamali Samaratunga
Journal:  BJU Int       Date:  2020-11-27       Impact factor: 5.588

4.  Research on Management Efficiency and Dynamic Relationship in Intelligent Management of Tourism Engineering Based on Industry 4.0.

Authors:  Tianchen Hou
Journal:  Comput Intell Neurosci       Date:  2022-01-22
  4 in total

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