Artificial neural networks in medical diagnosis
Top Cited Papers
- 31 July 2013
- journal article
- Published by University of South Bohemia in Ceske Budejovice in Journal of Applied Biomedicine
- Vol. 11 (2) , 47-58
- https://doi.org/10.2478/v10136-012-0031-x
Abstract
An extensive amount of information is currently available to clinical specialists, ranging from details ofclinical symptoms to various types of biochemical data and outputs of imaging devices. Each type of dataprovides information that must be evaluated and assigned to a particular pathology during the diagnosticprocess. To streamline the diagnostic process in daily routine and avoid misdiagnosis, artificial intelligencemethods (especially computer aided diagnosis and artificial neural networks) can be employed. Theseadaptive learning algorithms can handle diverse types of medical data and integrate them into categorizedoutputs. In this paper, we briefly review and discuss the philosophy, capabilities, and limitations of artificialneural networks in medical diagnosis through selected examplesKeywords
This publication has 46 references indexed in Scilit:
- Finding biomarkers is getting easierEcotoxicology, 2012
- Inverse optimal neural control of blood glucose level for type 1 diabetes mellitus patientsJournal of the Franklin Institute, 2012
- Automatic small bowel tumor diagnosis by using multi-scale wavelet-based analysis in wireless capsule endoscopy imagesBioMedical Engineering OnLine, 2012
- Artificial neural networks for closed loop control of in silico and ad hoc type 1 diabetesComputer Methods and Programs in Biomedicine, 2011
- Diagnosis of hypoglycemic episodes using a neural network based rule discovery systemExpert Systems with Applications, 2011
- Feed Forward Artificial Neural Network: Tool for Early Detection of Ovarian CancerScientia Pharmaceutica, 2011
- Artificial Neural Networks for Classification in Metabolomic Studies of Whole Cells Using1H Nuclear Magnetic ResonanceJournal of Biomedicine and Biotechnology, 2010
- Computational Intelligence in Early Diabetes Diagnosis: A ReviewThe Review of Diabetic Studies, 2010
- Training neural network classifiers for medical decision making: The effects of imbalanced datasets on classification performancePublished by Elsevier ,2007
- Neural networks for modelling of chemical reaction systems with complex kinetics: oxidation of 2-octanol with nitric acidChemical Engineering and Processing - Process Intensification, 2000