ABSTRACT
Intelligent clinical data analytics is concerned with the discovery of new diseases, disease diagnosis, identification of new biomarkers, dosage for better recovery and reduced toxicity, development of new vaccines, better patient care, study of patients' survivability and risk factor using artificial intelligence techniques and statistical analysis. Clinical data classification facilitates: the identification of the factors that increase the risk of getting disease or side-effect while other parameters are unchanged and the identification of the medication effectiveness for recovery from a disease state. Biostatistics is used to derive and validate certain hypothesis related to the nature of specific diseases, biomarkers, spread of diseases, recovery in response to a medication and the dosages of a medication for the appropriate response. Meta-analysis uses statistical techniques to combine the findings of similar test-studies. A clinical decision support system is an intelligent system that generates pertinent information based upon inputted patient data to suggest a course of actions.
