https://www.selleckchem.com/pr....oducts/isoxazole-9-i
Predicting outcome after aneurysmal subarachnoid hemorrhage (aSAH) is known to be challenging and complex. Machine learning approaches, of which feedforward artificial neural networks (ffANNs) are the most widely used, could contribute to the patient-specific outcome prediction. To investigate the prediction capacity of an ffANN for the patient-specific clinical outcome and the occurrence of delayed cerebral ischemia (DCI) and compare those results with the predictions of 2 internationally used scoring systems. A prospective d
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