A Medical-History-Based Potential Disease Prediction Algorithm

Abstract

As an important application of medical informatization, healthcare big data analysis has been extensively researched in the fields of intelligent consultation, disease diagnosis, intelligent question-answering doctors, and medical assistant decision support, and have made many achievements. In order to improve the comprehensiveness and pertinence of the medical examination, this paper intends to use healthcare big data analysis combined with deep learning technology to provide patients with potential diseases which is usually neglected for lacking of professional knowledge, so that patients can do targeted medical examinations to prevent health condition from getting worse. Inspired by the existing recommendation methods, this paper proposes a novel deep-learning-based hybrid recommendation algorithm, which is called medical-history-based potential disease prediction algorithm. The algorithm predicts the patient's possible disease based on the patient's medical history, providing a reference to patients and doctors to reduce the problem of delaying treatment due to unclear description of the symptom or limited professional knowledge. The experimental results show that our approach improves the accuracy of the potential diseases prediction.

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