Literature DB >> 19544548

Decision support systems for morphology-based diagnosis and prognosis of prostate neoplasms: a methodological approach.

Rodolfo Montironi1, Liang Cheng, Antonio Lopez-Beltran, Roberta Mazzucchelli, Marina Scarpelli, Peter H Bartels.   

Abstract

Recent advances in computer and information technologies have allowed the integration of both numeric and non-numeric data, that is, descriptive, linguistic terms. This has led at 1 end of the spectrum of technology development to machine vision based on image understanding and, at the other, to decision support systems. This has had a significant impact on our capability to derive diagnostic and prognostic information from histopathological material with prostate neoplasms. Cancer 2009;115(13 suppl):3068-77. (c) 2009 American Cancer Society.

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Year:  2009        PMID: 19544548     DOI: 10.1002/cncr.24345

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


  3 in total

Review 1.  Nuclear morphometry, nucleomics and prostate cancer progression.

Authors:  Robert W Veltri; Christhunesa S Christudass; Sumit Isharwal
Journal:  Asian J Androl       Date:  2012-04-16       Impact factor: 3.285

2.  Macroscopic morphology for estimation of malignant potential in pancreatic neuroendocrine neoplasm.

Authors:  Eriko Katsuta; Atsushi Kudo; Takumi Akashi; Yusuke Mitsunori; Satoshi Matsumura; Arihiro Aihara; Daisuke Ban; Takanori Ochiai; Shinji Tanaka; Yoshinobu Eishi; Minoru Tanabe
Journal:  J Cancer Res Clin Oncol       Date:  2016-02-17       Impact factor: 4.553

3.  SurfaceSlide: a multitouch digital pathology platform.

Authors:  Yinhai Wang; Kate E Williamson; Paul J Kelly; Jacqueline A James; Peter W Hamilton
Journal:  PLoS One       Date:  2012-01-23       Impact factor: 3.240

  3 in total

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