How Can Apache Spark Be Utilized in Cancer Research?
Apache Spark can be leveraged in several ways to advance cancer research. The most prominent uses include:
Genomic Data Analysis: Spark can handle large-scale genomic datasets efficiently, facilitating the identification of genetic mutations and patterns associated with different types of cancer. Predictive Modeling: By using machine learning libraries like MLlib in Spark, researchers can build predictive models to forecast cancer progression and treatment outcomes. Clinical Data Integration: Spark can merge disparate clinical data sources, enabling comprehensive analyses that can lead to more personalized treatment plans.
