Automated development of artificial neural networks for clinical purposes: Application for predicting the outcome of choledocholithiasis surgery.

Among various expert systems (ES), Artificial Neural Network (ANN) has shown to be suitable for the diagnosis of concurrent common bile duct stones (CBDS) in patients undergoing elective cholecystectomy. However, their application in practice remains limited since the development of ANNs represents a slow process that requires additional expertize from potential users. The aim of this study was to propose an ES for automated development of ANNs and validate its performances on the problem of prediction of CBDS.

Enrichment of live unlabelled cardiomyocytes from heterogeneous cell populations using manipulation of cell settling velocity by magnetic field.

The majority of available cardiomyocyte markers are intercellular proteins, limiting our ability to enrich live cardiomyocytes from heterogeneous cell preparations in the absence of genetic labeling. Here, we describe enrichment of live cardiomyocytes from the hearts of adult mice in a label-free microfluidic approach. The separation device consisted of a vertical column (15 mm long, 700 μm diameter), placed between permanent magnets resulting in a field strength of 1.