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An optimized experimental protocol based on neuro-evolutionary algorithms application to the classification of dyspeptic patients and to the prediction of the effectiveness of their treatment

Artificial intelligence in medicine, 2005-07, Vol.34 (3), p.279-305

2005

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Improved artificial neural networks in prediction of malignancy of lesions in contrast-enhanced MR-mammography

Medical physics (Lancaster), 2003-09, Vol.30 (9), p.2350-2359

2003

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Assessment of the Role of Genetic Polymorphism in Venous Thrombosis Through Artificial Neural Networks

Annals of human genetics, 2005-11, Vol.69 (6), p.693-706

2005

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ARTIFICIAL NEURAL NETWORK (ANN) VS. ROCKALL SCORE FOR PREDICTION OF MORTALITY IN PATIENTS WITH NON VARICEAL UPPER GI BLEEDING (UGIB)

Digestive and liver disease, 2009, Vol.41, p.S6-S6

2009

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P.169 PREDICTIVE FACTORS OF RELEVANT ENDOSCOPIC FINDINGS IN ELDERLY PATIENTS AT UPPER ENDOSCOPY

Digestive and liver disease, 2010, Vol.42, p.S162-S162

2010

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OC.11.1 PREDICTIVE FACTORS OF RELEVANT ENDOSCOPIC FINDINGS IN PATIENTS WITH A REGULAR USE OF NSAIDS

Digestive and liver disease, 2010, Vol.42, p.S95-S95

2010

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P.170 PREDICTIVE RULES TO SELECT UNINVESTIGATED AND UNCOMPLICATED DYSPEPTIC PATIENTS FOR UPPER ENDOSCOPY

Digestive and liver disease, 2010, Vol.42, p.S162-S163

2010

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Contribution of artificial neural networks to the classification and treatment of patients with uninvestigated dyspepsia

Digestive and liver disease, 2003-04, Vol.35 (4), p.222-231

2003

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Artificial neural network assessment of substitutive pharmacological treatments in hospitalised intravenous drug users

Artificial intelligence in medicine, 2002, Vol.24 (1), p.37-49

2002

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Artificial neural networks allow the use of simultaneous measurements of Alzheimer disease markers for early detection of the disease

Journal of translational medicine, 2005-07, Vol.3 (1), p.30-30, Article 30

2005

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Artificial neural networks accurately predict mortality in patients with nonvariceal upper GI bleeding

Gastrointestinal endoscopy, 2011-02, Vol.73 (2), p.218-226.e2

2011

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Use of Artificial Networks in Clinical Trials: A Pilot Study to Predict Responsiveness to Donepezil in Alzheimer's Disease

Journal of the American Geriatrics Society (JAGS), 2002-11, Vol.50 (11), p.1857-1860

2002

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Artificial neural networks are able to recognize gastro-oesophageal reflux disease patients solely on the basis of clinical data

European journal of gastroenterology & hepatology, 2005-06, Vol.17 (6), p.605-610

2005

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Artificial neural networks and artificial organisms can predict Alzheimer pathology in individual patients only on the basis of cognitive and functional status

Neuroinformatics (Totowa, N.J.), 2004, Vol.2 (4), p.399-416

2004

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Recognition of patients with cardiovascular disease by artificial neural networks

Annals of medicine (Helsinki), 2004, Vol.36 (8), p.630-640

2004

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An optimized experimental protocol based on neuro-evolutionary algorithms

Artificial intelligence in medicine, 2005-07, Vol.34 (3), p.279-305

2005

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Sistemi ACM e Imaging Diagnostico: Le Immagini Mediche Come Matrici Attive Di Connessioni

2006., 2005

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Artificial Neural Networks for Drug Vulnerability Recognition and Dynamic Scenarios Simulation

Substance use & misuse, 1998-01, Vol.33 (3), p.587-623

1998

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Artificial neural networks for drug vulnerability recognition and dynamic scenarios simulation: Artificial neural networks and complex social systems. III. Applications

Substance use & misuse, 1998, Vol.33 (3), p.587-623

1998

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ANNS in the recognition of refluxer and non refluxer gerd patients only on the basis of clinical data

Digestive and liver disease, 2001-11, Vol.33, p.A51-A51

2001

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Application of Artificial Neural Networks to Eating Disorders

Substance use & misuse, 1998-01, Vol.33 (3), p.765-791

1998

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Application of artificial neural networks to eating disorders: Artificial neural networks and complex social systems. III. Applications

Substance use & misuse, 1998, Vol.33 (3), p.765-791

1998

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Appropriateness Guidelines and Predictive Rules to Select Patients for Upper Endoscopy: A Nationwide Multicenter Study

The American journal of gastroenterology, 2010-06, Vol.105 (6), p.1327-1337

2010

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An optimized experimental protocol based on neuro-evolutionary algorithms application to the classification of dyspeptic patients and to the prediction of the effectiveness of their treatment

Improved artificial neural networks in prediction of malignancy of lesions in contrast-enhanced MR-mammography

Assessment of the Role of Genetic Polymorphism in Venous Thrombosis Through Artificial Neural Networks

ARTIFICIAL NEURAL NETWORK (ANN) VS. ROCKALL SCORE FOR PREDICTION OF MORTALITY IN PATIENTS WITH NON VARICEAL UPPER GI BLEEDING (UGIB)

P.169 PREDICTIVE FACTORS OF RELEVANT ENDOSCOPIC FINDINGS IN ELDERLY PATIENTS AT UPPER ENDOSCOPY

OC.11.1 PREDICTIVE FACTORS OF RELEVANT ENDOSCOPIC FINDINGS IN PATIENTS WITH A REGULAR USE OF NSAIDS

P.170 PREDICTIVE RULES TO SELECT UNINVESTIGATED AND UNCOMPLICATED DYSPEPTIC PATIENTS FOR UPPER ENDOSCOPY

Contribution of artificial neural networks to the classification and treatment of patients with uninvestigated dyspepsia

Artificial neural network assessment of substitutive pharmacological treatments in hospitalised intravenous drug users

Artificial neural networks allow the use of simultaneous measurements of Alzheimer disease markers for early detection of the disease

Artificial neural networks accurately predict mortality in patients with nonvariceal upper GI bleeding

Use of Artificial Networks in Clinical Trials: A Pilot Study to Predict Responsiveness to Donepezil in Alzheimer's Disease

Artificial neural networks are able to recognize gastro-oesophageal reflux disease patients solely on the basis of clinical data

Artificial neural networks and artificial organisms can predict Alzheimer pathology in individual patients only on the basis of cognitive and functional status

Recognition of patients with cardiovascular disease by artificial neural networks

An optimized experimental protocol based on neuro-evolutionary algorithms

Sistemi ACM e Imaging Diagnostico: Le Immagini Mediche Come Matrici Attive Di Connessioni

Artificial Neural Networks for Drug Vulnerability Recognition and Dynamic Scenarios Simulation

Artificial neural networks for drug vulnerability recognition and dynamic scenarios simulation: Artificial neural networks and complex social systems. III. Applications

ANNS in the recognition of refluxer and non refluxer gerd patients only on the basis of clinical data

Application of Artificial Neural Networks to Eating Disorders

Application of artificial neural networks to eating disorders: Artificial neural networks and complex social systems. III. Applications

Appropriateness Guidelines and Predictive Rules to Select Patients for Upper Endoscopy: A Nationwide Multicenter Study

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