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Artificiella neurala nätverk underlättar svåra medicinska beslut. Exempel från pankreatologin.

Bartosch-Härlid, Anna LU ; Andersson, Bodil LU ; Nilsson, Johan A; Aho, Ursula LU and Andersson, Roland LU (2009) In Läkartidningen 106(39). p.2446-2448
Abstract
Artificial neural networks (ANNs) is a nonlinear pattern recognition technique inspired by the function of the human brain. ANNs have been used successfully in analysis of complex medical relationships, for example prognostic predictions of various forms of cancer. Acute pancreatitis and pancreatic cancer are commonly recognized to be extremely difficult conditions in making diagnostic and prognostic predictions with traditional methods. The two pancreatic disorders thus represent suitable candidates for analysis by ANNs. We hereby present a systematic review of the applications of ANNs in the treatment of acute pancreatitis and pancreatic cancer.
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Pancreatitis: diagnosis, Pancreatic Neoplasms: therapy, Pancreatic Neoplasms: diagnosis, Pancreatic Neoplasms: mortality, Pancreatitis: mortality, Pancreatitis: therapy
in
Läkartidningen
volume
106
issue
39
pages
2446 - 2448
publisher
Sveriges Läkarförbund
external identifiers
  • pmid:19852163
  • scopus:70350441293
ISSN
0023-7205
language
Swedish
LU publication?
yes
id
f0f250af-d35d-48e3-90eb-e2fa695f83f4 (old id 1500043)
alternative location
http://www.ncbi.nlm.nih.gov/pubmed/19852163?dopt=Abstract
http://ltarkiv.lakartidningen.se/artNo37043
date added to LUP
2009-11-03 09:41:55
date last changed
2017-01-01 07:51:26
@article{f0f250af-d35d-48e3-90eb-e2fa695f83f4,
  abstract     = {Artificial neural networks (ANNs) is a nonlinear pattern recognition technique inspired by the function of the human brain. ANNs have been used successfully in analysis of complex medical relationships, for example prognostic predictions of various forms of cancer. Acute pancreatitis and pancreatic cancer are commonly recognized to be extremely difficult conditions in making diagnostic and prognostic predictions with traditional methods. The two pancreatic disorders thus represent suitable candidates for analysis by ANNs. We hereby present a systematic review of the applications of ANNs in the treatment of acute pancreatitis and pancreatic cancer.},
  author       = {Bartosch-Härlid, Anna and Andersson, Bodil and Nilsson, Johan A and Aho, Ursula and Andersson, Roland},
  issn         = {0023-7205},
  keyword      = {Pancreatitis: diagnosis,Pancreatic Neoplasms: therapy,Pancreatic Neoplasms: diagnosis,Pancreatic Neoplasms: mortality,Pancreatitis: mortality,Pancreatitis: therapy},
  language     = {swe},
  number       = {39},
  pages        = {2446--2448},
  publisher    = {Sveriges Läkarförbund},
  series       = {Läkartidningen},
  title        = {Artificiella neurala nätverk underlättar svåra medicinska beslut. Exempel från pankreatologin.},
  volume       = {106},
  year         = {2009},
}