Applications of Artificial Neural Networks in Medical Science
Computer technology has been advanced tremendously and the interest has been increased for the potential use of ‘Artificial Intelligence (AI)’ in medicine and biological research. One of the most interesting and extensively studied branches of AI is the ‘Artificial Neural Networks (ANNs)’. Basically, ANNs are the mathematical algorithms, generated by computers. ANNs learn from standard data and capture the knowledge contained in the data. Trained ANNs approach the functionality of small biological neural cluster in a very fundamental manner. They are the digitized model of biological brain and can detect complex nonlinear relationships between dependent as well as independent variables in a data where human brain may fail to detect. Nowadays, ANNs are widely used for medical applications in various disciplines of medicine especially in cardiology. ANNs have been extensively applied in diagnosis, electronic signal analysis, medical image analysis and radiology. ANNs have been used by many authors for modeling in medicine and clinical research. Applications of ANNs are increasing in pharmacoepidemiology and medical data mining. In this paper, authors have summarized various applications of ANNs in medical science.
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Document Type: Research Article
Publication date: September 1, 2007
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- Current Clinical Pharmacology publishes frontier reviews on all the latest advances in clinical pharmacology. The journal's aim is to publish the highest quality review articles in the field. Topics covered include: pharmacokinetics; therapeutic trials; adverse drug reactions; drug interactions; drug metabolism; pharmacoepidemiology; and drug development. The journal is essential reading for all researchers in clinical pharmacology.
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