2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023 - 2023 : Making Sense of Big Data: Diagnostic Predictions Using Deep Learning

Dr. Saifuddin, Mohtaram and Dr. Mariani, Mohd Dahlan and Dr. Noor Maizatulshima, Muhammad Sabri (2023) 2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023 - 2023 : Making Sense of Big Data: Diagnostic Predictions Using Deep Learning. 2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023. pp. 1655-1661. ISSN 979-835035776-9

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Abstract

This summary is targeted at making the experience of extensive records using deep learning for diagnostic predictions. The purpose is to develop a deep getting-to-know structure to manner big, heterogeneous, and noisy biomedical information units so that it will accurately identify and diagnose diseases. An efficient and robust deep-gaining knowledge of architecture is proposed, consisting of several convolutional layers and entirely related layers. A dataset of classified biomedical facts is used for training the model, and a validation dataset is used to test the model's performance. Upon successful training, the model can make more accurate and reliable sickness analysis predictions than existing fashions. Moreover, this deep gaining knowledge of structure can be prolonged to different medical prognosis tasks and is an effective tool for making sense of large, excessive-dimensional massive data units.

Item Type:	Article
Uncontrolled Keywords:	biomedical; experience; performance; predictions; summary
Divisions:	Institute of Graduate Studies (IGS)
Depositing User:	LIBRARY2 UPTM
Date Deposited:	09 Jul 2025 00:59
Last Modified:	09 Jul 2025 00:59
URI:	http://eprints.kuptm.edu.my/id/eprint/4792

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