Predicting the Cerebral Blood Flow Change Condition during Brain Strokes using Feature Fusion of FMRI Images and Clinical Features
- Title
- Predicting the Cerebral Blood Flow Change Condition during Brain Strokes using Feature Fusion of FMRI Images and Clinical Features
- Creator
- Sharma V.; Sinha A.; Wiryaseputra M.; Kumar B.; Kumar T.R.; Alkhayyat A.
- Description
- By fusing clinical information with functional magnetic resonance imaging (fFMRI) pictures, this study describes a novel method for predicting changes in cerebral blood flow during brain strokes. The FMRI data and patient-specific variables, such as age, gender, and medical history, are combined via feature fusion in the proposed technique. As a result, the model developed can accurately forecast changes in cerebral blood flow that occur during brain strokes. The efficiency of the suggested strategy is shown by experimental findings. The performance of the model is greatly enhanced when FMRI data and clinical characteristics are combined as opposed to just one data source. The findings of this study have important ramifications for increasing the accuracy of stroke diagnosis and treatment and, eventually, for bettering patient outcomes. The experimental results showed that the proposed method a high level of accuracy in predicting changes in cerebral blood flow after brain strokes. The performance of the model was much enhanced by combining clinical characteristics with FMRI data as opposed to using only one of these data sources. This emphasizes the value of including pertinent clinical information in the diagnosis and management of stroke. 2023 IEEE.
- Source
- 2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023
- Date
- 2023-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- deep learning; feature fusion; Imaging; prediction; strokes
- Coverage
- Sharma V., Christ University, Institute of Information Technology, Delhi Campus, India; Sinha A., Ignou, Department of Computer Science and Information Technology, New Delhi, India; Wiryaseputra M., Soegijapranata Catholic University, Semarang, Indonesia; Kumar B., Amity Univeristy, Department of Computer Science, Jharkhand, India; Kumar T.R., Iit Madras, Computational Mathematics & Data Science, India; Alkhayyat A., The Islamic University, College of Technical Engineering, Najaf, Iraq
- Rights
- Restricted Access
- Relation
- ISBN: 979-835033509-5
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Sharma V.; Sinha A.; Wiryaseputra M.; Kumar B.; Kumar T.R.; Alkhayyat A., “Predicting the Cerebral Blood Flow Change Condition during Brain Strokes using Feature Fusion of FMRI Images and Clinical Features,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/19728.