Contemporary applications of big data in science(1)

Bilal Hussain Malik
18/04/25
                                     Contemporary applications of big data in science


                                      Precision Medicine and Genomics
Big data is an underpinning of precision medicine, which shapes healthcare according to individual genetic, environmental, and lifestyle differences. Through examining enormous quantities of genomic data, healthcare professionals are able to identify genetic mutations and biomarkers for specific diseases. Genomic sequencing of millions of patients generates gigantic datasets that are analyzed by machine learning in order to predict disease risk and recommend personalized treatments. This is especially groundbreaking in oncology, with therapies being tailored to the genetic signature of a patient's tumor. Further, real-time integration of EHRs, environmental data, and wearable device outputs helps in disease diagnosis at an early stage and continuous health monitoring. Big data also accelerates drug discovery by pattern analysis in gigantic datasets, which reduces clinical trial time and expense. Projects like the National Institutes of Health's All of Us program demonstrate the potential for big health data to revolutionize personalized care. Big data also enables identifying health trends in whole populations, improving preventive care and public policy. Overall, big data-enabled precision medicine not only enhances the effectiveness of treatment but also shifts healthcare practice from being reactive to proactive, leading to better outcomes and reduced spending in healthcare systems.

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