Natural language processing in Mining Electronic Health records for Cancer insights

Abstract

A data-driven revolution has been made possible by the digitization of healthcare through the use of Electronic Health Records (EHRs), which provide a comprehensive database of patient information. Natural language processing (NLP) has the potential to completely transform cancer treatment through this treasure trove of data. The significant influence of NLP on EHR mining for cancer insights is examined in this abstract. NLP is the connecting thread between machine comprehension and the unstructured narratives found in EHRs. NLP serves as a catalyst for converting qualitative data into useful insights, from automating data extraction to revealing hidden patterns in clinical records. By using an iterative process, the standard of cancer care is continuously improved by taking into account practical observations. But there are issues that need to be resolved, like data privacy, medical terminology standardization, and the requirement for big, varied datasets. To overcome these obstacles and realize the full promise of natural language processing (NLP) in cancer treatment, cooperation between stakeholders including data scientists, medical experts, and policymakers is essential. Research found that there is a plethora of opportunities ahead for the integration of NLP and EHRs in the search for cancer insights. NLP's incorporation into cancer care represents a promising new chapter in the history of healthcare as we find ourselves at the crossroads of technology and medicine. a day when each cancer patient receives timely, tailored interventions that are based on knowledge gained from the massive quantity of electronic health data. NLP has the potential to be a revolutionary force that changes the oncology landscape and enhances the lives of cancer patients by ongoing cooperation, innovation, and a dedication to moral data practices.