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NSU Technologies

Statistical Model for Predicting Falling in Humans

Dr. Patrick Hardigan has created a unique mathematical/statistical modeling approach, leveraging Latent Class Analysis that aggregates large data-sets of biomedical factors to identify those subset of factors that are most associated with the probability of falling. The biomedical factors include active disease states, clinical findings, number of medications, types of medications, age, etc. more

Specific Inhibitors for Vascular Endothelial Growth Factor Receptors

Doctors Rathinavelu, Pattabiraman, Sridhar, and Dakshanamurthy, through in-silico screening, have identified a novel class of small molecules, substituted isoindoles, that inhibit vascular endothelial growth factor receptor (VEGFR inhibitors). more

Method and Kit for Delivering Regenerative Endodontic Treatment

Doctors Murray and Garcia-Godoy developed isolation and cell culturing techniques for obtaining and proliferating adult dental pulp stem cells. These cells have been shown to replace diseased tooth pulp after root canal. more