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An Augmented Artificial Intelligence Approach for Chronic Diseases Prediction

Rashid, Junaid; Batool, Saba; Kim, Jungeun; Wasif Nisar, Muhammad; Hussain, Amir; Juneja, Sapna; Kushwaha, Riti


Junaid Rashid

Saba Batool

Jungeun Kim

Muhammad Wasif Nisar

Sapna Juneja

Riti Kushwaha


Chronic diseases are increasing in prevalence and mortality worldwide. Early diagnosis has therefore become an important research area to enhance patient survival rates. Several research studies have reported classification approaches for specific disease prediction. In this paper, we propose a novel augmented artificial intelligence approach using an artificial neural network (ANN) with particle swarm optimization (PSO) to predict five prevalent chronic diseases including breast cancer, diabetes, heart attack, hepatitis, and kidney disease. Seven classification algorithms are compared to evaluate the proposed model's prediction performance. The ANN prediction model constructed with a PSO based feature extraction approach outperforms other state-of-the-art classification approaches when evaluated with accuracy. Our proposed approach gave the highest accuracy of 99.67%, with the PSO. However, the classification model's performance is found to depend on the attributes of data used for classification. Our results are compared with various chronic disease datasets and shown to outperform other benchmark approaches. In addition, our optimized ANN processing is shown to require less time compared to random forest (RF), deep learning and support vector machine (SVM) based methods. Our study could play a role for early diagnosis of chronic diseases in hospitals, including through development of online diagnosis systems.


Rashid, J., Batool, S., Kim, J., Wasif Nisar, M., Hussain, A., Juneja, S., & Kushwaha, R. (2022). An Augmented Artificial Intelligence Approach for Chronic Diseases Prediction. Frontiers in Public Health, 10, Article 860396.

Journal Article Type Article
Acceptance Date Feb 22, 2022
Online Publication Date Mar 31, 2022
Publication Date 2022
Deposit Date May 12, 2022
Publicly Available Date May 12, 2022
Publisher Frontiers Media
Peer Reviewed Peer Reviewed
Volume 10
Article Number 860396
Keywords medical diagnosis, feature selection, chronic diseases, artificial neural network (ANN), prediction
Public URL


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