Evaluation of the Bias in the Management of Patient’s Appointments in a Pediatric Office

Abstract

The application of Machine Learning algorithms must always take into account the objectives set within the project, the characteristics of the domain where the project will be carried out and the data available to use. Given this, it is essential before collecting data considered as representative of the problem to be solved, because otherwise there may be hidden biases in the data and these may solve a different problem from the one intended. In this context, the aim of this work is to apply a process based on the Gridding method that allows the analysis of the features of the data to be used. This process is applied to the historical data of a pediatric medical office where it is sought to implement an intelligent system that allows to predict the number of normal and over-shift appointments for a particular date and time, since it is desired to hire, when necessary, another pediatric doctor to assist in the care of patients.

Keywords

• Intelligent Systems
• Machine Learning
• Training Data
• Repertory Grid
• Bias