Literature DB >> 17275425

International experience on the use of artificial neural networks in gastroenterology.

E Grossi1, A Mancini, M Buscema.   

Abstract

In this paper, we reconsider the scientific background for the use of artificial intelligence tools in medicine. A review of some recent significant papers shows that artificial neural networks, the more advanced and effective artificial intelligence technique, can improve the classification accuracy and survival prediction of a number of gastrointestinal diseases. We discuss the 'added value' the use of artificial neural networks-based tools can bring in the field of gastroenterology, both at research and clinical application level, when compared with traditional statistical or clinical-pathological methods.

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Year:  2007        PMID: 17275425     DOI: 10.1016/j.dld.2006.10.003

Source DB:  PubMed          Journal:  Dig Liver Dis        ISSN: 1590-8658            Impact factor:   4.088


  18 in total

1.  The use of fast molecular descriptors and artificial neural networks approach in organochlorine compounds electron ionization mass spectra classification.

Authors:  Maciej Przybyłek; Waldemar Studziński; Alicja Gackowska; Jerzy Gaca
Journal:  Environ Sci Pollut Res Int       Date:  2019-07-30       Impact factor: 4.223

2.  Artificial intelligence techniques applied to the development of a decision-support system for diagnosing celiac disease.

Authors:  Josceli Maria Tenório; Anderson Diniz Hummel; Frederico Molina Cohrs; Vera Lucia Sdepanian; Ivan Torres Pisa; Heimar de Fátima Marin
Journal:  Int J Med Inform       Date:  2011-09-13       Impact factor: 4.046

3.  Polymorphisms in folate-metabolizing genes, chromosome damage, and risk of Down syndrome in Italian women: identification of key factors using artificial neural networks.

Authors:  Fabio Coppedè; Enzo Grossi; Francesca Migheli; Lucia Migliore
Journal:  BMC Med Genomics       Date:  2010-09-24       Impact factor: 3.063

4.  Contrast-enhanced ultrasonography parameters in neural network diagnosis of liver tumors.

Authors:  Costin Teodor Streba; Mihaela Ionescu; Dan Ionut Gheonea; Larisa Sandulescu; Tudorel Ciurea; Adrian Saftoiu; Cristin Constantin Vere; Ion Rogoveanu
Journal:  World J Gastroenterol       Date:  2012-08-28       Impact factor: 5.742

5.  Artificial Adaptive Systems and predictive medicine: a revolutionary paradigm shift.

Authors:  Enzo Grossi
Journal:  Immun Ageing       Date:  2010-12-16       Impact factor: 6.400

6.  Prediction of effect of pegylated interferon alpha-2b plus ribavirin combination therapy in patients with chronic hepatitis C infection.

Authors:  Tetsuro Takayama; Hirotoshi Ebinuma; Shinichiro Tada; Yoshiyuki Yamagishi; Kanji Wakabayashi; Keisuke Ojiro; Takanori Kanai; Hidetsugu Saito; Toshifumi Hibi
Journal:  PLoS One       Date:  2011-12-02       Impact factor: 3.240

7.  Computer-Aided Prediction of Long-Term Prognosis of Patients with Ulcerative Colitis after Cytoapheresis Therapy.

Authors:  Tetsuro Takayama; Susumu Okamoto; Tadakazu Hisamatsu; Makoto Naganuma; Katsuyoshi Matsuoka; Shinta Mizuno; Rieko Bessho; Toshifumi Hibi; Takanori Kanai
Journal:  PLoS One       Date:  2015-06-25       Impact factor: 3.240

8.  Outcome predictors in autism spectrum disorders preschoolers undergoing treatment as usual: insights from an observational study using artificial neural networks.

Authors:  Antonio Narzisi; Filippo Muratori; Massimo Buscema; Sara Calderoni; Enzo Grossi
Journal:  Neuropsychiatr Dis Treat       Date:  2015-06-30       Impact factor: 2.570

9.  Application of artificial neural networks to investigate one-carbon metabolism in Alzheimer's disease and healthy matched individuals.

Authors:  Fabio Coppedè; Enzo Grossi; Massimo Buscema; Lucia Migliore
Journal:  PLoS One       Date:  2013-08-12       Impact factor: 3.240

10.  Predicting rotator cuff tears using data mining and Bayesian likelihood ratios.

Authors:  Hsueh-Yi Lu; Chen-Yuan Huang; Chwen-Tzeng Su; Chen-Chiang Lin
Journal:  PLoS One       Date:  2014-04-14       Impact factor: 3.240

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