Predictive Intelligent System Development for Disease Classification in Diagnostic Applications

Abstract

With ever increasing explosion in information domain and demand for highest accuracy in medical diagnosis, the existence of a reliable, accurate prediction system is the need of the hour. In this work, an effective prediction system has been developed for accurate classification of undifferentiated ailments using a unique approach. Prediction of undifferentiated diseases at an early stage always helps in better diagnosis. Illnesses like tuberculosis, non-tubercular bacterial infection, dengue fever, non-infectious diseases have regular manifestation of fever. In present work, the uniqueness lies in the use of only temperature data of the patient being referred in predicting the nature of fever, with highest degree of accuracy, instead of several self-defined parameters over limited interval of time. The system has been developed based on artificial intelligent technique, and optimization has been achieved by assessing the performance of different classifiers available. Using prediction model with classifiers, decision can take over comparative results between different classifier algorithms. A result of predictive system defines the combination of good classifier and system developed. Accuracy score and other salient parameters describe the complete picture of the system. Predictive model development in this work proved to be one of the best assistant tools to a doctor to take call over the disease crucial period. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.