Open Access
Research Article
The scalable cloud-based reinforcement learning for multimedia data in cognitive Neuroscience for secure healthcare analysis
Venkateswara Rao Bollavenki.bolla@gmail.comDepartment of Computer Science Engineering (AI & ML) St. Martin’s Engineering College DhulapallySecunderabad, Telangana, 500100, India0000-0002-8812-0909View full profile → , B. Vikasvikasboddu30@gmail.comDepartment of Computer Science and Engineering Sreenidhi University GhatkesarHyderabad, Telangana, 501301, India0000-0002-4040-1189View full profile → , *Sirisha PotluriCorresponding authorsirisha.vegunta@gmail.comDepartment of Computer Science and Engineering Koneru Lakshmaiah Education Foundation BowrampetHyderabad, Telangana, 500043, India0000-0001-9106-9780View full profile → , Yerragudipadu Subbarayudusubbu.jntua@gmail.comDepartment of Computer Science and Engineering Koneru Lakshmaiah Education Foundation BowrampetHyderabad, Telangana, 500043, India0000-0003-0349-9831View full profile → , G. Sucharithasucharithasu@gmail.comDepartment of Computer Science and Engineering Anurag University Venkatapur VillageHyderabad, Telangana, 500088, India0000-0001-7861-2451View full profile → , Nirmalajyothi Narisettynirmala.narisetty@klh.edu.inDepartment of Computer Science and Engineering Koneru Lakshmaiah Education Foundation BowrampetHyderabad, Telangana, 500043, India0000-0002-4810-9676View full profile →
* Corresponding author · click or hover a name for details
- Received:
- 10 Dec 2024
- Published Online:
- 01 Sep 2025
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIOS-2008
- Pages:
- 1793–1801
Abstract
Recently, the field of neuroscience and the complexity of brain research data have increased due to advancements in imaging technologies, electrophysiological recordings, and genetic sequencing. Managing and organizing this vast amount of data is a big challenge. Our research explores the integration or participation of cloud-based multimedia data systems in cognitive neuroscience and brain research, emphasizing their role in data storage, security, retrieval, encryption, and analysis. Technology addresses these challenges, providing data storage and more efficient data analysis methods. As neuroscience continues to evolve, generating increasingly complex datasets, the role of multimedia data systems becomes crucial in unlocking brain functions and understanding neurological disorders. Additionally, cloud-based multimedia data systems offer scalable and cost-effective solutions for storing and processing large neuroscience datasets. Reinforcement learning (RL) approaches are gradually being explored for healthcare applications, especially neuroscience. The proposed RL algorithm is devised to learn and acquire optimal actions via a trial-and-error methodology steered by rewards or penalties. The proposed RL model transforms cognitive and neural procedures into formal scientific structures. This facilitates realizing and modeling how the brain can learn from events and generate decisions. Results and outcomes demonstrate that the proposed model outperforms the existing state-of-the-art models.
Keywords
Subject Classifications
68U1068M2092C55
References
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