[Prediction of renal transplantation outcome using artificial neural networks and investigating important risk factors].

Background: Renal Transplantation is the final choice for some patients with ESRD (End-Stage Renal Disease), but some transplantations suffer from acute or chronic rejection, so its very important to predict the outcome of transplantation.

Method: s. The dataset was extracted from records of 4572 patients with kidney transplantations.

Rapid identification of bacteria by the pattern of redox reactions rate using 2',7'-dichlorodihydrofluorescein diacetate.

Bacterial infection is a life-threatening situation, and its rapid diagnosis is essential for treatment. Apart from medical applications, rapid identification of bacteria is vital in the food industry or the public health system. There are various bacterial identification techniques, including molecular-based methods, immunological approaches, and biosensor-based procedures.