Neural Networks: What Are They?

摘要

Editorials1 December 1991Neural Networks: What Are They?Michael R. J. Guerriere, MD, Allan S. Detsky, MD, PhDMichael R. J. Guerriere, MD, Allan S. Detsky, MD, PhDAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-115-11-906 SectionsAboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail ExcerptFor centuries, mankind has sought to understand and duplicate the processes that constitute intelligence. The advent of modern computer technology, with its ability to perform many complex tasks far better and faster than the brain, has led many to predict that this quest would soon be completed.Modern computers are based entirely on a central processor that adds and multiplies binary numbers. All tasks handled by computers including calculations, word processing, and robot control are done by translating them into these binary operations. Information is stored in banks of storage elements called registers, which are separate from the processing elements....References1. Searle J. Is the brain's mind a computer program? Sci Am. 1990; 262(1):26-31. CrossrefMedlineGoogle Scholar2. ChurchlandChurchland PP. Could a machine think? Sci Am. 1990;262(1):32-7. CrossrefMedlineGoogle Scholar3. MinskyPapert MS. Perceptrons. Cambridge, Massachusetts: MIT Press; 1969. Google Scholar4. RumelhartHintonWilliams DGR. Learning internal representations by error propagation. In: Rumelhart DE, McClelland JL; eds. Parallel Distributed Processing, v 1. Cambridge, Massachusetts: MIT Press; 1988:318-62. Google Scholar5. Baxt W. Use of an artificial neural network for the diagnosis of myocardial infarction. Ann Intern Med. 1991;115:843-8. LinkGoogle Scholar6. Baxt W. Use of an artificial neural network for data analysis in clinical decision-making: the diagnosis of acute coronary occlusion. Neural Computation. 1990;2:480-9. CrossrefGoogle Scholar7. HartWyatt AJ. Evaluating black-boxes as medical decision aids: issues arising from a study of neural networks. Medical Inf. (Lond). 1990;15:229-36. MedlineGoogle Scholar8. Meistrell M. Evaluation of neural network performance by receiver operating characteristic (ROC) analysis: examples form the biotechnology domain. Comput Methods Programs Biomed. 1990; 32:73-80. CrossrefMedlineGoogle Scholar9. SpitzerHassounWangBearden AMCF. Signal decomposition and diagnostic classification of the electromyogram using a novel neural network technique. Proceedings of the 14th Annual Symposium on Computer Applications in Medical Care. 1990;552-6. Google Scholar10. DytchWied HG. Artificial neural networks and their use in quantitative pathology. Anal Quant Cytol Histol. 1990;12:379-93. MedlineGoogle Scholar11. BooneGrossGreco-Hunt JGV. Neural networks in radiologic diagnosis. Invest Radiol. 1990;25:1012-23. CrossrefMedlineGoogle Scholar12. WaibelHampshire AJ. Building blocks for speech: modular neural networks are a new approach to high-performance speech recognition. Byte. 1989;14(8):235-42. Google Scholar13. . Byte. 1989; 14(8):244-5. Google Scholar This content is PDF only. To continue reading please click on the PDF icon. Author, Article, and Disclosure InformationAffiliations: PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetails Metrics Cited ByEarly Warning Models to Estimate the 30-Day Mortality Risk After Stent Placement for Patients with Malignant Biliary ObstructionStatistical and machine learning methodology for abdominal aortic aneurysm prediction from ultrasound screeningsArtificial neural networks predict the incidence of portosplenomesenteric venous thrombosis in patients with acute pancreatitisApplying a Hybrid Model of Markov Chain and Logistic Regression to Identify Future Urban Sprawl in Abouelreesh, Aswan: A Case StudyA combined neural network and genetic algorithm based approach for optimally designed femoral implant having improved primary stabilityAssessing the Predictive Utility of Logistic Regression, Classifi