In this analytical process it revolves around data and findings related to what has happened already in the past. The process involves collecting historical data and presenting the data in an organized manner for easy understanding. It uses statistical methods such as regressions, deviations, K-means clustering, vector methods, bayesian classifications etc. to understand the patient’s stage.
Here we develop Predictive analytical solutions, a sort of data analysis that forecasts potential future occurrences and outcomes using probabilities.It aids healthcare organizations in the evaluation and training of practitioners, the detection of scan anomalies, and the forecasting of disease epidemics using sophisticated statistical approaches such as decision trees, covariance, isolation points, etc. for a accurate diagnostics.
It is a stage of data analysis that forecasts potential future occurrences and outcomes using probabilities and data that are derived from patient data analysis and predictive models. We recommend the best actionables for the patient’s problem or difficulties. This kind of data analytics determines the best course of action using procedure and tools such as Power BI, Tableau, Splunk, etc. To get the findings, we architect and use these data tools and frameworks to build complex algorithms that solve and achieve results.
