abstract: this paper represents a novel use of artificial neural networks in medical science. the proposed technique involves training a multi layer perceptron (mlp) (a kind of artificial neural network) with a bp learning algorithm to recognize a pattern for the diagnosing and prediction of five blood disorders, through the results of blood tests from h1 machine. the blood test parameters and ...

normal 0 false false false en-us x-none ar-sa microsoftinternetexplorer4 the physical interaction of proteins which lead to compiling them into large densely connected networks is a noticeable subject to investigation. protein interaction networks are useful because of making basic scientific abstraction and improving biological and biomedical applications. based on principle roles of proteins ...

Unraveling complex molecular interactions and networks and incorporating clinical information in modeling will present a paradigm shift in molecular medicine. Embedding biological relevance via modeling molecular networks and pathways has become increasingly important for biomarker identification in cancer susceptibility and metastasis studies. Here, we give a comprehensive overview of computat...

Cancer is a complex disease resulting from alterations of multiple signaling networks. Cancer networks have been identified as scale-free networks and may contain a functionally important key player called a hub that is linked to a large number of interactors. Since a hub can serve as a biological marker in a given network, targeting the hub could be an effective strategy for enhancing the effi...

b a c k g r o u n d & aim: one of the common used models in time series is auto regressive integrated moving  average  (arima)  model.  arima  will  do  modeling  only  linearly.  artificial  neural networks (ann) are modern methods that be used for time series forecasting.  these models can identify non-linear relationships  among data. the breast cancer has the most mortality of cancers among...

every woman is at risk of ovarian cancer; about 90 percent of women who develop ovarian cancer are above 40 years of age, with the high number of ovarian cancers occurring at the age of 60 years and above. early and correct diagnosis of ovarian cancer can allow proper treatment and as a result reduce the mortality rate. in this paper, we proposed a hybrid of synthetic minority over-sampling tec...