A data-driven approach to allogeneic stem cell transplantation

Abstract

Background: Healthcare organizations today are capable of generating and collecting large amounts of data. This increase in volumeof data requires automatic way for these data to be extracted and analyzed when needed. Millions of people would like to store cellspecimens, for use in all sorts of contingencies. This study explores innovations in life sciences sector with the case of stem cells, anemerging and promising field. Stem cells research plays a key role in regenerative medicine because of the variable potentials it offersin basic, clinical research and development. Methodology: Applications from the stem cell research and developments can be categorizedinto four key fields as the application of the pluripotent cells, application in the field of drug discovery, cell therapy and diagnosis forexample in identifying new treatment options forany organ failure or any fatal disease. Stem cells have the unique ability to become anycell in the body. This can keep on renewing themselves. These basic building blocks of life are fast becoming the ultimate repair-kit ofthe future. Results: Statistics show that there is a greater chance for success in a stem cell transplant between siblings (syngenic) as wellas there may be chance to solve the disease of unrelated donors (allogenic) and recipients. Conclusion: Basing on these findings, it canbe concluded that the data-driven approach to retrieve the knowledge from the stem cell database helps to solve the disease of unrelateddonors and recipients also. This offers a new insight to the data mining techniques in the field of medical practices.