Computer methods and programs in biomedicine
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Comput Methods Programs Biomed · Mar 2017
A novel end-to-end classifier using domain transferred deep convolutional neural networks for biomedical images.
Highly accurate classification of biomedical images is an essential task in the clinical diagnosis of numerous medical diseases identified from those images. Traditional image classification methods combined with hand-crafted image feature descriptors and various classifiers are not able to effectively improve the accuracy rate and meet the high requirements of classification of biomedical images. The same also holds true for artificial neural network models directly trained with limited biomedical images used as training data or directly used as a black box to extract the deep features based on another distant dataset. In this study, we propose a highly reliable and accurate end-to-end classifier for all kinds of biomedical images via deep learning and transfer learning. ⋯ We propose a robust automated end-to-end classifier for biomedical images based on a domain transferred deep convolutional neural network model that shows a highly reliable and accurate performance which has been confirmed on several public biomedical image datasets.
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Comput Methods Programs Biomed · Mar 2017
Computational simulation of passive leg-raising effects on hemodynamics during cardiopulmonary resuscitation.
The passive leg-raising (PLR) maneuver has been used for patients with circulatory failure to improve hemodynamic responsiveness by increasing cardiac output, which should also be beneficial and may exert synergetic effects during cardiopulmonary resuscitation (CPR). However, the impact of the PLR maneuver on CPR remains unclear due to difficulties in monitoring cardiac output in real-time during CPR and a lack of clinical evidence. ⋯ We developed a CPR-PLR model and demonstrated the effects of PLR on hemodynamics by investigating changes in CO, SPP, and CPP under different compression rates and angles of leg raising. Our computational model will facilitate study of PLR effects during CPR and the development of an advanced model combined with circulatory disorders, which will be a valuable asset for further studies.
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Comput Methods Programs Biomed · Mar 2017
Determinants and development of a web-based child mortality prediction model in resource-limited settings: A data mining approach.
Improving child health and reducing child mortality rate are key health priorities in developing countries. This study aimed to identify determinant sand develop, a web-based child mortality prediction model in Ethiopian local language using classification data mining algorithm. ⋯ In this study, nearly accurate results were obtained by employing decision tree and rule induction techniques. Determinants are identified and a web-based child mortality prediction model in Ethiopian local language is developed. Thus, the result obtained could support child health intervention programs in Ethiopia where trained human resource for health is limited. Advanced classification algorithms need to be tested to come up with optimal models.