Advances in Multimodal Fusion of EHR and Medical Imaging Data Using deep learning techniques for advanced treatment of brain cancer

In this research, the performance of different deep learning models, including CNN + RNN, VGG16 + RNN, VGG19 + RNN, ResNet50 + RNN, and InceptionV3 + RNN in predicting brain tumour grades by employing Electronic Health Record (EHR) and imaging data are evaluated. Confusion matrices show the models' abilities to predict, showing the results of the prediction capability of each model over tumour grades. From the result and analysis, InceptionV3+RNN is performing better than all other ML models. With the multimodal fusion techniques, an informed decision can be made about the grades of the cancer cells, and the clinicians can give the proper treatment to the patients. The proposed approach can be implemented in real-time to predict the cancer grades with the highest level of accuracy for better treatment.

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Publication Details

Published
2024-10-11
DOI
https://doi.org/10.1145/3708597.3708613
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.00
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article

Advances in Multimodal Fusion of EHR and Medical Imaging Data Using deep learning techniques for advanced treatment of brain cancer

Siva Raja, S. Vidhya, R. Sumithra, Kavita Ramanan et al.
Brain Tumor Detection and Classification
article

Advances in Multimodal Fusion of EHR and Medical Imaging Data Using deep learning techniques for advanced treatment of brain cancer

Siva Raja, S. Vidhya, R. Sumithra, Kavita Ramanan, S Anjana, K. Rejini
article en

Abstract

In this research, the performance of different deep learning models, including CNN + RNN, VGG16 + RNN, VGG19 + RNN, ResNet50 + RNN, and InceptionV3 + RNN in predicting brain tumour grades by employing Electronic Health Record (EHR) and imaging data are evaluated. Confusion matrices show the models' abilities to predict, showing the results of the prediction capability of each model over tumour grades. From the result and analysis, InceptionV3+RNN is performing better than all other ML models. With the multimodal fusion techniques, an informed decision can be made about the grades of the cancer cells, and the clinicians can give the proper treatment to the patients. The proposed approach can be implemented in real-time to predict the cancer grades with the highest level of accuracy for better treatment.

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Openalex Percentile: Top 69%
Brain Tumor Detection and Classification
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