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  • ISSN[Online] : 2643-9875  ||  ISSN[Print] : 2643-9840

Volume 07 Issue 03 March 2024

Deep Neural Network Based Disease Prediction Analysis
1Chuan Zeng, 2Xiaoyang Zhang, 3Hao Yang, 4Bobo Liu
1,2,3,4School of Management Science and Engineering,Anhui University of Finance & Economics,Bengbu Anhui, 233030, China
DOI : https://doi.org/10.47191/ijmra/v7-i03-52

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ABSTRACT:

With the rapid development of social and economic construction as well as medical informatization, the medical industry has gradually entered the era of big data and artificial intelligence, using the medical big data accumulated in the hospital information system for pooling, modeling, analysis, and the use of neural networks can predict and determine the type of patient's disease and the source of the cause, which can not only reduce the complexity of the disease diagnostic test but also achieve the effect of predictive diagnosis, and provide theoretical basis and practical experience for the establishment, improvement and practical application of the intelligent medical system. It provides theoretical basis and practical experience for the establishment, improvement and practical application of intelligent medical system.

KEYWORDS:

neural network,Disease Prediction,big data technology,artificial intelligence (AI) technology,intelligent medical care

REFERENCES
1) New AI Algorithm Accurately Predicts and Diagnoses Alzheimer's Disease [J]. Clinical OMICs, 2020, 7 (3): 4-4

2) Baseer K ,Sivakumar K ,Veeraiah D , et al. Healthcare diagnostics with an adaptive deep learning model integrated with the Internet of medical Things (IoMT) for predicting heart disease [J]. Biomedical Signal Processing and Control, 2024, 92 105988-.

3) Li X ,Wang Z ,Zhao W , et al. Machine learning algorithm for predict the in-hospital mortality in critically ill patients with congestive heart failure combined with chronic kidney disease. [J]. Renal failure, 2024, 46 (1): 2315298-2315298.

4) Şaylık F ,Kümet Ö ,Sarıkaya R , et al. Bendopnea Predicts High SYNTAX Score in Patients With Coronary Artery Disease: A Bayesian Approach. [J]. Angiology, 2024, 33197241235957-33197241235957.
Volume 07 Issue 03 March 2024

There is an Open Access article, distributed under the term of the Creative Commons Attribution – Non Commercial 4.0 International (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/), which permits remixing, adapting and building upon the work for non-commercial use, provided the original work is properly cited.


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