As health care delivery is dependent on accurate and detailed clinical data, an important activity of the healthcare data analytics and technology approaches to be used is to facilitate access to the clinical data available through the medical records and enhance the quality of this information. The categorization and accuracy of the information extracted or detected determines the accuracy of clinical outcomes. the logical step of doing relation mapping is to extract data from medical records/reports/charts and recognize them to relate it to a structured coded form. Often, this translation mapping is considered text categorization.Text classifiers can be built to automatically detect and extract the medical condition features in the medical reports and convert them into predefined medical codes or terms. The healthcare experts and knowledge and information technology scientists are adopting to the new age technologies like Machine learning/ Natural language processing for formulating inductive learning algorithms, in the pursuit of automatically generating classifiers for clinical reports.