Fig 2 illustrates the overall review process including number of articles excluded at each stage. 11. e0212356. Its application is particularly valuable under one or more of several conditions: when sample data show complex interaction effects or do not meet parametric assumptions, when the relationship between independent and dependent variables is not strong, when there is a large unexplained variance in information, or in situations where the theoretical basis of prediction is poorly understood . The main activities involved in the KDD process include (i) integration and cleaning, (ii) selection and transformation, (iii) data mining and (iv) evaluation and interpretation. Though they may seem like a futuristic concept, ANNs have been used in healthcare for several decades. The Journal of Artificial Neural Networks is an academic journal – hosted by OMICS International – a pioneer in open access publishing–and is listed among the top 10 journals in artificial neural networks. ANNs are going to need some tweaking if they’re going to become the change that the healthcare industry needs. 13. Han et al. The most successful applications of ANN are found in extremely complex medical situations . departmental or organizational level) where patient preference may be important but not essential; and on a wider (macro) level by large groups or public organizations related to allocation or utilization of resources where decisions are based on public interest and reflective of society as a whole . Prior to 2006, application of neural networks included processing of biomedical signals, for example image and speech processing [89, 90], clinical diagnosis, image analysis and interpretation, and drug development . Although lacking the ability to explain decision-making, ANN-based decision-support tools enable health care organizational decision-makers to respond to complex and emergent environments using incoming and evolving data. Also referred to as the generalized delta rule, backpropagation refers to how an ANN is trained or ‘learns’ based on data. Investigation, The brain has neurons process information in the form of electric signals. These units are arranged in a series of layers that together constitute the whole Artificial Neural Networks in a system. Policies encouraging transparency and sharing of core datasets across public and private sectors can stimulate higher levels of innovation-oriented competition and research productivity . Table 2 lists the main topic areas of articles reviewed. As suggested by the literature, the most commonly used taxonomy of ANN found was the feed-forward neural network. An Artificial Neural Network (ANN) is an information-processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. A neural network is a network of artificial neurons programmed in software. Prior efforts have concentrated on a specific domain or aspect of health care and/or limited study findings to a period of time. They may require lengthy training times and the use of random weight initializations may lead to different solutions . Publication dates ranged from 1997 to 2018 with the number of studies fluctuating each year (Fig 3A). A few years later, the ability of neural networks to learn any type of function was demonstrated , suggesting capabilities of neural networks as universal approximators . Preliminary diagnosis of high-risk patients (for disease or attributes) using neural networks provide hospital administrators with a cost-effective tool in time and resource management . Writing – review & editing, Affiliations budget, resource allocation, technology acquisition, service additions/reductions, strategic planning) . artificial neural networks, electronic health record, data mining. Drug development – Finally, ANNs are used in the development of drugs for various conditions – working by using large amounts of data to come to conclusions about treatment options. A unit sends information to other unit from which it does not receive any … … Main topics or area of interest based on the article’s overall purpose included Organizational Behaviour (18%), Cardiovascular (14%), Infectious Disease and Telemedicine (7%) (Table 2). An artificial neural networks approach in managing healthcare. Yes organizing or distinguishing data by relevant categories or concepts) , using a hybrid learning approach for automatic tissue recognition in wound images for accurate wound evaluations , and comparison of soft-computing techniques for diagnosis of heart conditions by processing digitally recorded heart sound signals to extract time and frequency features related to normal and abnormal heart conditions . 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