Articles
Deep Learning-based Analysis of Electronic Health Records for Disease Diagnosis: Utilizing deep learning techniques to analyze electronic health records and aid in disease diagnosis
Published 27-09-2024
Keywords
- Recurrent Neural Networks,
- Healthcare
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
How to Cite
[1]
Dr. Michael Petrov, “Deep Learning-based Analysis of Electronic Health Records for Disease Diagnosis: Utilizing deep learning techniques to analyze electronic health records and aid in disease diagnosis”, Hong Kong J. of AI and Med., vol. 4, no. 2, pp. 1–8, Sep. 2024, Accessed: Sep. 18, 2024. [Online]. Available: https://hongkongscipub.com/index.php/hkjaim/article/view/33
Abstract
The use of deep learning in healthcare, particularly for analyzing electronic health records (EHRs) to aid in disease diagnosis, has shown promising results in recent years. This paper explores the application of deep learning techniques, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), in processing EHR data for disease diagnosis. We discuss the challenges and opportunities in utilizing EHRs for deep learning-based diagnosis and present a comprehensive review of existing literature. Additionally, we provide insights into the future directions of this field, including the potential for personalized medicine and improved patient outcomes.
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