Juniper Publishers-Biomedical Engineering Journals

Controlling Informative Features for Improved Accuracy and Faster Predictions in Omentum Cancer Models Authored by Damian R Mingle  Identification of suitable biomarkers for accurate prediction of phenotypic outcomes is a goal for personalized medicine. However, current machine learning approaches are either too complex or perform poorly. Here, a novel feature detection and engineering machine-learning framework is presented to address this need. First, the Rip Curl process is applied which generates a set of 10 additional features. Second, we rank all features including the Rip Curl features from which the top-ranked will most likely contain the most informative features for prediction of the underlying biological classes. The top-ranked features are used in model building. This process creates for more expressive features which are captured in models with an eye towards the model learning from increasing sample amount and the accuracy/time results. The perform

Advances in the Therapy of Advanced Ovarian Cancer-Special Emphasis on the PD1/PDL1 Pathway Authored By Kulvinder Kochar Kaur, Ovarian Cancer gets diagnosed in advanced stage in 75% of patient and thus remains one of the most lethal gynecological malignancies. Despite 80% patients being responsive to platinum based chemotherapies to start with most relapse finally. Hence need of the hour is to find more effective immunotherapy’s to be added to these CRT. Programmed cell death1 (PD1) -PDL1 is an important immune pathway which is discussed in detail along with role of nivelumab (a monoclonal antibody against PD1) and addition of other immunotherapy’s like bevacizumab, Olafarib (A PARP (polyadenosine diphosphate (ADP)-ribose- inhibitor), C edinarib (a VEGF123 inhibitor) etc to increase five year survival. Reasons of why success not obtained as expected is further sought through Effect of IFNγ on PDL1 pathway and different NK cellular phenotypes is further analyzed besides