Effect of Marine Phycotoxins on Pediatric Neurological Health

Authors

  • Srihari Padmanabhan Independent Researcher,USA.
  • Ojaswin Tharan Independent Researcher,USA.

DOI:

https://doi.org/10.36676/jrps.v15.i2.1551

Keywords:

marine phycotoxins, paediatric neurology, neurotoxicity, HABs, neurodevelopment, toxins

Abstract

Phycotoxins are toxic substances which are generated by varieties of algae; marine phycotoxins are particularly dangerous to the neurological welfare of children. The types of marine phycotoxins, their neurotoxic action, and the management of exposure in children are all examined in this paper. It is just in this case that the patient undergoes early evaluation of signs of a chronic illness, and the prevention of the worsening of the condition and its impact on the neurological system. In total, the present research aims at analyzing the short and the long-term effects of the mentioned toxins with the purpose of providing a broad look at the risks they present to neurodevelopment of children.

References

Ugandhar Dasi. (2024). Developing A Cloud-Based Natural Language Processing (NLP) Platform for Sentiment Analysis and Opinion Mining of Social Media Data. International Journal of Intelligent Systems and Applications in Engineering, 12(22s), 165–174. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6406

Dasi, U., Singla, N., Balasubramanian, R., Benadikar, S., & Shanbhag, R. R. (2024). Ethical implications of AI-driven personalization in digital media. Journal of Informatics Education and Research, 4(3), 588-593.

Nikhil Singla. (2023). Assessing the Performance and Cost-Efficiency of Serverless Computing for Deploying and Scaling AI and ML Workloads in the Cloud. International Journal of Intelligent Systems and Applications in Engineering, 11(5s), 618–630. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6730

Ugandhar Dasi, Nikhil Singla, Rajkumar Balasubramanian, Siddhant Benadikar, Rishabh Rajesh Shanbhag. (2024). Analyzing the Security and Privacy Challenges in Implementing Ai and Ml Models in Multi-Tenant Cloud Environments. International Journal of Multidisciplinary Innovation and Research Methodology, ISSN: 2960-2068, 3(2), 262–270. Retrieved from https://ijmirm.com/index.php/ijmirm/article/view/108

Balasubramanian, R., Benadikar, S., Shanbhag, R. R., Dasi, U., & Singla, N. (2024). Investigating the application of reinforcement learning algorithms for autonomous resource management in cloud computing environments. African Journal of Biological Sciences, 6(14), 6451-6480. https://doi.org/10.48047/AFJBS.6.14.2024.6451-6480

Rishabh Rajesh Shanbhag, Rajkumar Balasubramanian, Ugandhar Dasi, Nikhil Singla, & Siddhant Benadikar. (2022). Case Studies and Best Practices in Cloud-Based Big Data Analytics for Process Control. International Journal for Research Publication and Seminar, 13(5), 292–311. https://doi.org/10.36676/jrps.v13.i5.1462 DOI: https://doi.org/10.36676/jrps.v13.i5.1462

Siddhant Benadikar. (2021). Developing a Scalable and Efficient Cloud-Based Framework for Distributed Machine Learning. International Journal of Intelligent Systems and Applications in Engineering, 9(4), 288 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6761

Siddhant Benadikar. (2021). Evaluating the Effectiveness of Cloud-Based AI and ML Techniques for Personalized Healthcare and Remote Patient Monitoring. International Journal on Recent and Innovation Trends in Computing and Communication, 9(10), 03–16. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/11036

Shanbhag, R. R., Benadikar, S., Dasi, U., Singla, N., & Balasubramanian, R. (2024). Investigating the application of transfer learning techniques in cloud-based AI systems for improved performance and reduced training time. Letters in High Energy Physics, 31.

Rishabh Rajesh Shanbhag. (2023). Exploring the Use of Cloud-Based AI and ML for Real-Time Anomaly Detection and Predictive Maintenance in Industrial IoT Systems. International Journal of Intelligent Systems and Applications in Engineering, 11(4), 925 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6762

Nikhil Singla. (2023). Assessing the Performance and Cost-Efficiency of Serverless Computing for Deploying and Scaling AI and ML Workloads in the Cloud. International Journal of Intelligent Systems and Applications in Engineering, 11(5s), 618–630. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/673

Nikhil Singla. (2023). Assessing the Performance and Cost-Efficiency of Serverless Computing for Deploying and Scaling AI and ML Workloads in the Cloud. International Journal of Intelligent Systems and Applications in Engineering, 11(5s), 618–630. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6730

Challa, S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2019). Investigating the use of natural language processing (NLP) techniques in automating the extraction of regulatory requirements from unstructured data sources. Annals of PharmaResearch, 7(5), 380-387.

Chaturvedi, R., & Sharma, S. (2024). Implementing Predictive Analytics for Proactive Revenue Cycle Management. Journal for Research in Applied Sciences and Biotechnology, 3(4), 74–78. https://doi.org/10.55544/jrasb.3.4.9 DOI: https://doi.org/10.55544/jrasb.3.4.9

Chaturvedi, R., Sharma, S., Pandian, P. K. G., & Sharma, S. (2024). Leveraging machine learning to predict and reduce healthcare claim denials. Zenodo. https://doi.org/10.5281/zenodo.13268360

Ritesh Chaturvedi. (2023). Robotic Process Automation (RPA) in Healthcare: Transforming Revenue Cycle Operations. International Journal on Recent and Innovation Trends in Computing and Communication, 11(6), 652–658. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/11045

Chaturvedi, R., & Sharma, S. (2022). Assessing the Long-Term Benefits of Automated Remittance in Large Healthcare Networks. Journal for Research in Applied Sciences and Biotechnology, 1(5), 219–224. https://doi.org/10.55544/jrasb.1.5.25

Chaturvedi, R., & Sharma, S. (2022). Enhancing healthcare staffing efficiency with AI-powered demand management tools. Eurasian Chemical Bulletin, 11(Regular Issue 1), 675-681. https://doi.org/10.5281/zenodo.13268360

Dr. Saloni Sharma, & Ritesh Chaturvedi. (2017). Blockchain Technology in Healthcare Billing: Enhancing Transparency and Security. International Journal for Research Publication and Seminar, 10(2), 106–117. Retrieved from https://jrps.shodhsagar.com/index.php/j/article/view/1475

Dr. Saloni Sharma, & Ritesh Chaturvedi. (2017). Blockchain Technology in Healthcare Billing: Enhancing Transparency and Security. International Journal for Research Publication and Seminar, 10(2), 106–117. Retrieved from https://jrps.shodhsagar.com/index.php/j/article/view/1475

Saloni Sharma. (2020). AI-Driven Predictive Modelling for Early Disease Detection and Prevention. International Journal on Recent and Innovation Trends in Computing and Communication, 8(12), 27–36. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/11046

Chaturvedi, R., & Sharma, S. (2022). Assessing the Long-Term Benefits of Automated Remittance in Large Healthcare Networks. Journal for Research in Applied Sciences and Biotechnology, 1(5), 219–224. https://doi.org/10.55544/jrasb.1.5.25 DOI: https://doi.org/10.55544/jrasb.1.5.25

Pavan Ogeti. (2024). Benefits and Challenges of Deploying Machine Learning Models in the Cloud. International Journal of Intelligent Systems and Applications in Engineering, 12(22s), 194–209. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6409

Pavan Ogeti, Narendra Sharad Fadnavis, Gireesh Bhaulal Patil, Uday Krishna Padyana, Hitesh Premshankar Rai. (2022). Blockchain Technology for Secure and Transparent Financial Transactions. European Economic Letters (EEL), 12(2), 180–188. Retrieved from https://www.eelet.org.uk/index.php/journal/article/view/1283

Ogeti, P., Fadnavis, N. S., Patil, G. B., Padyana, U. K., & Rai, H. P. (2023). Edge computing vs. cloud computing: A comparative analysis of their roles and benefits. Volume 20, No. 3, 214-226.

Fadnavis, N. S., Patil, G. B., Padyana, U. K., Rai, H. P., & Ogeti, P. (2020). Machine learning applications in climate modeling and weather forecasting. NeuroQuantology, 18(6), 135-145. https://doi.org/10.48047/nq.2020.18.6.NQ20194

Narendra Sharad Fadnavis. (2021). Optimizing Scalability and Performance in Cloud Services: Strategies and Solutions. International Journal on Recent and Innovation Trends in Computing and Communication, 9(2), 14–21. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10889

Gireesh Bhaulal Patil. (2022). AI-Driven Cloud Services: Enhancing Efficiency and Scalability in Modern Enterprises. International Journal of Intelligent Systems and Applications in Engineering, 10(1), 153–162. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6728

Padyana, U. K., Rai, H. P., Ogeti, P., Fadnavis, N. S., & Patil, G. B. (2023). AI and Machine Learning in Cloud-Based Internet of Things (IoT) Solutions: A Comprehensive Review and Analysis. Integrated Journal for Research in Arts and Humanities, 3(3), 121–132. https://doi.org/10.55544/ijrah.3.3.20

Patil, G. B., Padyana, U. K., Rai, H. P., Ogeti, P., & Fadnavis, N. S. (2021). Personalized marketing strategies through machine learning: Enhancing customer engagement. Journal of Informatics Education and Research, 1(1), 9. http://jier.org

Padyana, U. K., Rai, H. P., Ogeti, P., Fadnavis, N. S., & Patil, G. B. (2023). AI and Machine Learning in Cloud-Based Internet of Things (IoT) Solutions: A Comprehensive Review and Analysis. Integrated Journal for Research in Arts and Humanities, 3(3), 121–132. https://doi.org/10.55544/ijrah.3.3.20 DOI: https://doi.org/10.55544/ijrah.3.3.20

Padyana, U. K., Rai, H. P., Ogeti, P., Fadnavis, N. S., & Patil, G. B. (2024). Predicting disease susceptibility with machine learning in genomics. Letters in High Energy Physics, 2024(20).

Uday Krishna Padyana, Hitesh Premshankar Rai, Pavan Ogeti, Narendra Sharad Fadnavis, & Gireesh Bhaulal Patil. (2024). Server less Architectures in Cloud Computing: Evaluating Benefits and Drawbacks. Innovative Research Thoughts, 6(3), 1–12. https://doi.org/10.36676/irt.v10.i3.1439 DOI: https://doi.org/10.36676/irt.v10.i3.1439

Rai, H. P., Ogeti, P., Fadnavis, N. S., Patil, G. B., & Padyana, U. K. (2024). AI-based forensic analysis of digital images: Techniques and applications in cybersecurity. Journal of Digital Economy, 2(1), 47-61.

Hitesh Premshankar Rai, Pavan Ogeti, Narendra Sharad Fadnavis, Gireesh Bhaulal Patil, & Uday Krishna Padyana. (2024). Integrating Public and Private Clouds: The Future of Hybrid Cloud Solutions. Universal Research Reports, 8(2), 143–153. https://doi.org/10.36676/urr.v9.i4.1320

Hitesh Premshankar Rai, Pavan Ogeti, Narendra Sharad Fadnavis, Gireesh Bhaulal Patil, & Uday Krishna Padyana. (2024). Integrating Public and Private Clouds: The Future of Hybrid Cloud Solutions. Universal Research Reports, 8(2), 143–153. https://doi.org/10.36676/urr.v9.i4.1320 DOI: https://doi.org/10.36676/urr.v9.i4.1320

Ugandhar Dasi. (2024). Developing A Cloud-Based Natural Language Processing (NLP) Platform for Sentiment Analysis and Opinion Mining of Social Media Data. International Journal of Intelligent Systems and Applications in Engineering, 12(22s), 165–174. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6406

Dasi, U., Singla, N., Balasubramanian, R., Benadikar, S., & Shanbhag, R. R. (2024). Ethical implications of AI-driven personalization in digital media. Journal of Informatics Education and Research, 4(3), 588-593.

Krishnateja Shiva. (2024). Natural Language Processing for Customer Service Chatbots: Enhancing Customer Experience. International Journal of Intelligent Systems and Applications in Engineering, 12(22s), 155–164. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6405

Krishnateja Shiva. (2022). Leveraging Cloud Resource for Hyperparameter Tuning in Deep Learning Models. International Journal on Recent and Innovation Trends in Computing and Communication, 10(2), 30–35. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10980

Shiva, K., Etikani, P., Bhaskar, V. V. S. R., Palavesh, S., & Dave, A. (2022). The rise of robo-advisors: AI-powered investment management for everyone. Journal of Namibian Studies, 31, 201-214.

Etikani, P., Bhaskar, V. V. S. R., Choppadandi, A., Dave, A., & Shiva, K. (2024). Forecasting climate change with deep learning: Improving climate modeling accuracy. African Journal of Bio-Sciences, 6(14), 3903-3918. https://doi.org/10.48047/AFJBS.6.14.2024.3903-3918

Etikani, P., Bhaskar, V. V. S. R., Nuguri, S., Saoji, R., & Shiva, K. (2023). Automating machine learning workflows with cloud-based pipelines. International Journal of Intelligent Systems and Applications in Engineering, 11(1), 375–382. https://doi.org/10.48047/ijisae.2023.11.1.375

Etikani, P., Bhaskar, V. V. S. R., Palavesh, S., Saoji, R., & Shiva, K. (2023). AI-powered algorithmic trading strategies in the stock market. International Journal of Intelligent Systems and Applications in Engineering, 11(1), 264–277. https://doi.org/10.1234/ijsdip.org_2023-Volume-11-Issue-1_Page_264-277

Shiva, K., Etikani, P., Bhaskar, V. V. S. R., Mittal, A., Dave, A., Thakkar, D., Kanchetti, D., & Munirathnam, R. (2024). Anomaly detection in sensor data with machine learning: Predictive maintenance for industrial systems. J. Electrical Systems, 20-10s, 454–462.

Bhaskar, V. V. S. R., Etikani, P., Shiva, K., Choppadandi, A., & Dave, A. (2019). Building explainable AI systems with federated learning on the cloud. Journal of Cloud Computing and Artificial Intelligence, 16(1), 1–14.

Ogeti, P., Fadnavis, N. S., Patil, G. B., Padyana, U. K., & Rai, H. P. (2022). Blockchain technology for secure and transparent financial transactions. European Economic Letters, 12(2), 180-192. http://eelet.org.uk

Vijaya Venkata Sri Rama Bhaskar, Akhil Mittal, Santosh Palavesh, Krishnateja Shiva, Pradeep Etikani. (2020). Regulating AI in Fintech: Balancing Innovation with Consumer Protection. European Economic Letters (EEL), 10(1). https://doi.org/10.52783/eel.v10i1.1810 DOI: https://doi.org/10.52783/eel.v10i1.1810

Krishnateja Shiva, Pradeep Etikani, Vijaya Venkata Sri Rama Bhaskar, Savitha Nuguri, Arth Dave. (2024). Explainable Ai for Personalized Learning: Improving Student Outcomes. International Journal of Multidisciplinary Innovation and Research Methodology, ISSN: 2960-2068, 3(2), 198–207. Retrieved from https://ijmirm.com/index.php/ijmirm/article/view/100

Dave, A., Shiva, K., Etikani, P., Bhaskar, V. V. S. R., & Choppadandi, A. (2022). Serverless AI: Democratizing machine learning with cloud functions. Journal of Informatics Education and Research, 2(1), 22-35. http://jier.org

Dave, A., Etikani, P., Bhaskar, V. V. S. R., & Shiva, K. (2020). Biometric authentication for secure mobile payments. Journal of Mobile Technology and Security, 41(3), 245-259.

Saoji, R., Nuguri, S., Shiva, K., Etikani, P., & Bhaskar, V. V. S. R. (2021). Adaptive AI-based deep learning models for dynamic control in software-defined networks. International Journal of Electrical and Electronics Engineering (IJEEE), 10(1), 89–100. ISSN (P): 2278–9944; ISSN (E): 2278–9952

Narendra Sharad Fadnavis. (2021). Optimizing Scalability and Performance in Cloud Services: Strategies and Solutions. International Journal on Recent and Innovation Trends in Computing and Communication, 9(2), 14–21. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10889

Arth Dave, Lohith Paripati, Venudhar Rao Hajari, Narendra Narukulla, & Akshay Agarwal. (2024). Future Trends: The Impact of AI and ML on Regulatory Compliance Training Programs. Universal Research Reports, 11(2), 93–101. Retrieved from https://urr.shodhsagar.com/index.php/j/article/view/1257

Joel lopes, Arth Dave, Hemanth Swamy, Varun Nakra, & Akshay Agarwal. (2023). Machine Learning Techniques And Predictive Modeling For Retail Inventory Management Systems. Educational Administration: Theory and Practice, 29(4), 698–706. https://doi.org/10.53555/kuey.v29i4.5645

Nitin Prasad. (2024). Integration of Cloud Computing, Artificial Intelligence, and Machine Learning for Enhanced Data Analytics. International Journal of Intelligent Systems and Applications in Engineering, 12(22s), 11–20. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6381

Nitin Prasad. (2022). Security Challenges and Solutions in Cloud-Based Artificial Intelligence and Machine Learning Systems. International Journal on Recent and Innovation Trends in Computing and Communication, 10(12), 286–292. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10750

Prasad, N., Narukulla, N., Hajari, V. R., Paripati, L., & Shah, J. (2020). AI-driven data governance framework for cloud-based data analytics. Volume 17, (2), 1551-1561.

Jigar Shah , Joel lopes , Nitin Prasad , Narendra Narukulla , Venudhar Rao Hajari , Lohith Paripati. (2023). Optimizing Resource Allocation And Scalability In Cloud-Based Machine Learning Models. Migration Letters, 20(S12), 1823–1832. Retrieved from https://migrationletters.com/index.php/ml/article/view/10652

Big Data Analytics using Machine Learning Techniques on Cloud Platforms. (2019). International Journal of Business Management and Visuals, ISSN: 3006-2705, 2(2), 54-58. https://ijbmv.com/index.php/home/article/view/76

Shah, J., Narukulla, N., Hajari, V. R., Paripati, L., & Prasad, N. (2021). Scalable machine learning infrastructure on cloud for large-scale data processing. Tuijin Jishu/Journal of Propulsion Technology, 42(2), 45-53. DOI: https://doi.org/10.52783/tjjpt.v42.i2.7166

Narukulla, N., Hajari, V. R., Paripati, L., Shah, J., Prasad, N., & Pandian, P. K. G. (2024). Edge computing and its role in enhancing artificial intelligence and machine learning applications in the cloud. J. Electrical Systems, 20(9s), 2958-2969.

Narukulla, N., Lopes, J., Hajari, V. R., Prasad, N., & Swamy, H. (2021). Real-time data processing and predictive analytics using cloud-based machine learning. Tuijin Jishu/Journal of Propulsion Technology, 42(4), 91-102 DOI: https://doi.org/10.52783/tjjpt.v42.i4.6757

Secure Federated Learning Framework for Distributed Ai Model Training in Cloud Environments. (2019). International Journal of Open Publication and Exploration, ISSN: 3006-2853, 7(1), 31-39. https://ijope.com/index.php/home/article/view/145

Lohith Paripati. (2024). Edge Computing for AI and ML: Enhancing Performance and Privacy in Data Analysis . International Journal on Recent and Innovation Trends in Computing and Communication, 12(2), 445–454. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10848

Paripati, L., Prasad, N., Shah, J., Narukulla, N., & Hajari, V. R. (2021). Blockchain-enabled data analytics for ensuring data integrity and trust in AI systems. International Journal of Computer Science and Engineering (IJCSE), 10(2), 27–38. ISSN (P): 2278–9960; ISSN (E): 2278–9979.

Arth Dave. (2024). Improving Financial Forecasting Accuracy with AI-Driven Predictive Analytics. International Journal of Intelligent Systems and Applications in Engineering, 12(21s), 3866 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6158

Hajari, V. R., Chaturvedi, R., Sharma, S., Tilala, M., & Chawda, A. D. (2024). Risk-based testing methodologies for FDA compliance in medical devices. African Journal of Biological Sciences, 6(Si4), 3949-3960. https://doi.org/10.48047/AFJBS.6.Si4.2024.3949-3960

Hajari, V. R., Prasad, N., Narukulla, N., Chaturvedi, R., & Sharma, S. (2023). Validation techniques for AI/ML components in medical diagnostic devices. NeuroQuantology, 21(4), 306-312. https://doi.org/10.48047/NQ.2023.21.4.NQ23029

Hajari, V. R., Chaturvedi, R., Sharma, S., Tilala, M., Chawda, A. D., & Benke, A. P. (2023). Interoperability testing strategies for medical IoT devices. Tuijin Jishu/Journal of Propulsion Technology, 44(1), 258.

DOI: 10.36227/techrxiv.171340711.17793838/v1 DOI: https://doi.org/10.36227/techrxiv.171340711.17793838/v1

Krishnateja Shiva. (2024). Natural Language Processing for Customer Service Chatbots: Enhancing Customer Experience. International Journal of Intelligent Systems and Applications in Engineering, 12(22s), 155–164. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6405

Shiva, K., Etikani, P., Bhaskar, V. V. S. R., Mittal, A., Dave, A., Thakkar, D., Kanchetti, D., & Munirathnam, R. (2024). Anomaly detection in sensor data with machine learning: Predictive maintenance for industrial systems. Journal of Electrical Systems, 20(10s), 454-462.

Kanchetti, D., Munirathnam, R., & Thakkar, D. (2024). Integration of Machine Learning Algorithms with Cloud Computing for Real-Time Data Analysis. Journal for Research in Applied Sciences and Biotechnology, 3(2), 301–306. https://doi.org/10.55544/jrasb.3.2.46

Challa, S. S. S., Chawda, A. D., Benke, A. P., & Tilala, M. (2023). Regulatory intelligence: Leveraging data analytics for regulatory decision-making. International Journal on Recent and Innovation Trends in Computing and Communication, 11, 10.

Challa, S. S. S., Chawda, A. D., Benke, A. P., & Tilala, M. (2024). Streamlining change control processes in regulatory affairs: Best practices and case studies. Integrated Journal for Research in Arts and Humanities, 4(4), 4. DOI: https://doi.org/10.55544/ijrah.4.4.12

Challa, S. S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2019). Investigating the use of natural language processing (NLP) techniques in automating the extraction of regulatory requirements from unstructured data sources. Annals of Pharma Research, 7(5),

Challa, S. S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2021). Navigating regulatory requirements for complex dosage forms: Insights from topical, parenteral, and ophthalmic products. NeuroQuantology, 19(12), 15.

Challa, S. S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2022). Quality management systems in regulatory affairs: Implementation challenges and solutions. Journal for Research in Applied Sciences and Biotechnology, 1(3), DOI: https://doi.org/10.55544/jrasb.1.3.36

Gajera, B., Shah, H., Parekh, B., Rathod, V., Tilala, M., & Dave, R. H. (2024). Design of experiments-driven optimization of spray drying for amorphous clotrimazole nanosuspension. AAPS PharmSciTech, 25(6), DOI: https://doi.org/10.1208/s12249-024-02871-1

Hajari, V. R., Chaturvedi, R., Sharma, S., Tilala, M., & Chawda, A. D. (2024). Risk-based testing methodologies for FDA compliance in medical devices. African Journal of Biological Sciences, 6(4),

Tilala, M. (2023). Real-time data processing in healthcare: Architectures and applications for immediate clinical insights. International Journal on Recent and Innovation Trends in Computing and Communication, 11, 20.

Tilala, M. H., Chenchala, P. K., Choppadandi, A., Kaur, J., Naguri, S., Saoji, R., & ... (2024). Ethical considerations in the use of artificial intelligence and machine learning in health care: A comprehensive review. Cureus, 16(6), 2.

Tilala, M., & Chawda, A. D. (2020). Evaluation of compliance requirements for annual reports in pharmaceutical industries. NeuroQuantology, 18(11), 27.

Tilala, M., Challa, S. S. S., Chawda, A. D., Pandurang, A., & Benke, D. S. S. (2024). Analyzing the role of real-world evidence (RWE) in supporting regulatory decision-making and post-marketing surveillance. African Journal of Biological Sciences, 6(14),

Tilala, M., Chawda, A. D., & Benke, A. P. (2023). Enhancing regulatory compliance through training and development programs: Case studies and recommendations. Journal of Cardiovascular Research, 14(11),

Ghavate, N. (2018). An Computer Adaptive Testing Using Rule Based. Asian Journal For Convergence In Technology (AJCT) ISSN -2350-1146, 4(I). Retrieved from http://asianssr.org/index.php/ajct/article/view/443

Shanbhag, R. R., Dasi, U., Singla, N., Balasubramanian, R., & Benadikar, S. (2020). Overview of cloud computing in the process control industry. International Journal of Computer Science and Mobile Computing, 9(10), 121-146. https://www.ijcsmc.com DOI: https://doi.org/10.47760/ijcsmc.2020.v09i10.016

Benadikar, S. (2021). Developing a scalable and efficient cloud-based framework for distributed machine learning. International Journal of Intelligent Systems and Applications in Engineering, 9(4), 288. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6761

Shanbhag, R. R., Benadikar, S., Dasi, U., Singla, N., & Balasubramanian, R. (2022). Security and privacy considerations in cloud-based big data analytics. Journal of Propulsion Technology, 41(4), 62-81.

Shanbhag, R. R., Balasubramanian, R., Benadikar, S., Dasi, U., & Singla, N. (2021). Developing scalable and efficient cloud-based solutions for ecommerce platforms. International Journal of Computer Science and Engineering (IJCSE), 10(2), 39-58.

Shanbhag, R. R. (2023). Accountability frameworks for autonomous AI decision-making systems. International Journal on Recent and Innovation Trends in Computing and Communication, 11(3), 565-569.

Tripathi, A. (2020). AWS serverless messaging using SQS. IJIRAE: International Journal of Innovative Research in Advanced Engineering, 7(11), 391-393. DOI: https://doi.org/10.26562/ijirae.2020.v0711.003

Tripathi, A. (2019). Serverless architecture patterns: Deep dive into event-driven, microservices, and serverless APIs. International Journal of Creative Research Thoughts (IJCRT), 7(3), 234-239. Retrieved from http://www.ijcrt.org

Tripathi, A. (2023). Low-code/no-code development platforms. International Journal of Computer Applications (IJCA), 4(1), 27–35. Retrieved from https://iaeme.com/Home/issue/IJCA?Volume=4&Issue=1

Tripathi, A. (2024). Unleashing the power of serverless architectures in cloud technology: A comprehensive analysis and future trends. IJIRAE: International Journal of Innovative Research in Advanced Engineering, 11(03), 138-146. DOI: https://doi.org/10.26562/ijirae.2024.v1103.01

Tripathi, A. (2024). Enhancing Java serverless performance: Strategies for container warm-up and optimization. International Journal of Computer Engineering and Technology (IJCET), 15(1), 101-106.

Tripathi, A. (2022). Serverless deployment methodologies: Smooth transitions and improved reliability. IJIRAE: International Journal of Innovative Research in Advanced Engineering, 9(12), 510-514. DOI: https://doi.org/10.26562/ijirae.2022.v0912.10

Tripathi, A. (2022). Deep dive into Java tiered compilation: Performance optimization. International Journal of Creative Research Thoughts (IJCRT), 10(10), 479-483. Retrieved from https://www.ijcrt.org

Kanchetti, D., Munirathnam, R., & Thakkar, D. (2024). Integration of Machine Learning Algorithms with Cloud Computing for Real-Time Data Analysis. Journal for Research in Applied Sciences and Biotechnology, 3(2), 301–306. https://doi.org/10.55544/jrasb.3.2.46 DOI: https://doi.org/10.55544/jrasb.3.2.46

Thakkar, D., & Kumar, R. (2024). AI-Driven Predictive Maintenance for Industrial Assets using Edge Computing and Machine Learning. Journal for Research in Applied Sciences and Biotechnology, 3(1), 363–367. https://doi.org/10.55544/jrasb.3.1.55 DOI: https://doi.org/10.55544/jrasb.3.1.55

Aravind Reddy Nayani, Alok Gupta, Prassanna Selvaraj, Ravi Kumar Singh, Harsh Vaidya. (2023). Online Bank Management System in Eclipse IDE: A Comprehensive Technical Study. European Economic Letters (EEL), 13(3), 2095–2113. Retrieved from https://www.eelet.org.uk/index.php/journal/article/view/1874

Aravind Reddy Nayani, Alok Gupta, Prassanna Selvaraj, Ravi Kumar Singh, & Harsh Vaidya. (2019). Search and Recommendation Procedure with the Help of Artificial Intelligence. International Journal for Research Publication and Seminar, 10(4), 148–166. https://doi.org/10.36676/jrps.v10.i4.1503 DOI: https://doi.org/10.36676/jrps.v10.i4.1503

Aravind Reddy Nayani, Alok Gupta, Prassanna Selvaraj, Ravi Kumar Singh, Harsh Vaidya. (2024). Chatbot Detection with the Help of Artificial Intelligence. International Journal of Multidisciplinary Innovation and Research Methodology, ISSN: 2960-2068, 3(3), 1–16. Retrieved from https://ijmirm.com/index.php/ijmirm/article/view/114

Harsh Vaidya, Aravind Reddy Nayani, Alok Gupta, Prassanna Selvaraj, & Ravi Kumar Singh. (2023). Using OOP Concepts for the Development of a Web-Based Online Bookstore System with a Real-Time Database. International Journal for Research Publication and Seminar, 14(5), 253–274. https://doi.org/10.36676/jrps.v14.i5.1502 DOI: https://doi.org/10.36676/jrps.v14.i5.1502

Vaidya, H., Nayani, A. R., Gupta, A., Selvaraj, P., & Singh, R. K. (2020). Effectiveness and future trends of cloud computing platforms. Tuijin Jishu/Journal of Propulsion Technology, 41(3). Retrieved from https://www.journal-propulsiontech.com

Harsh Vaidya, Aravind Reddy Nayani, Alok Gupta, Prassanna Selvaraj, & Ravi Kumar Singh. (2024). The Impact of Emerging Technologies (e.g., AI, Blockchain, IoT) on Conceptualizing and Delivering New Business Offerings. Journal of Computational Analysis and Applications (JoCAAA), 33(05), 233–242. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/493

Singh, R. K., Vaidya, H., Nayani, A. R., Gupta, A., & Selvaraj, P. (2024). AI-driven multi-modal demand forecasting: Combining social media sentiment with economic indicators and market trends. Journal of Informatics Education and Research, 4(3), 1298. Retrieved from http://jier.org

Ravi Kumar Singh, Harsh Vaidya, Aravind Reddy Nayani, Alok Gupta, Prassanna Selvaraj. (2024). AI-Driven Machine Learning Techniques and Predictive Analytics for Optimizing Retail Inventory Management Systems. European Economic Letters (EEL), 13(1), 410–425. https://doi.org/10.52783/eel.v14i3.1903 DOI: https://doi.org/10.52783/eel.v14i3.1903

Ravi Kumar Singh, Harsh Vaidya, Aravind Reddy Nayani, Alok Gupta, & Prassanna Selvaraj. (2024). Development of Student Result Management System Using Java as Backend. International Journal of Communication Networks and Information Security (IJCNIS), 16(1 (Special Issue), 1109–1121. Retrieved from https://www.ijcnis.org/index.php/ijcnis/article/view/6983

Prassanna Selvaraj, Ravi Kumar Singh, Harsh Vaidya, Aravind Reddy Nayani, Alok Gupta. (2023). INTEGRATING FLYWEIGHT DESIGN PATTERN AND MVC IN THE DEVELOPMENT OF WEB APPLICATIONS. International Journal of Communication Networks and Information Security (IJCNIS), 15(1), 245–249. Retrieved from https://ijcnis.org/index.php/ijcnis/article/view/7068

Selvaraj, P. . (2022). Library Management System Integrating Servlets and Applets Using SQL Library Management System Integrating Servlets and Applets Using SQL database. International Journal on Recent and Innovation Trends in Computing and Communication, 10(4), 82–89. https://doi.org/10.17762/ijritcc.v10i4.11109 DOI: https://doi.org/10.17762/ijritcc.v10i4.11109

Prassanna Selvaraj. (2024). Implementation of an Airline Ticket Booking System Utilizing Object-Oriented Programming and Its Techniques. International Journal of Intelligent Systems and Applications in Engineering, 12(11s), 694–705. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6856

Gupta, A., Selvaraj, P., Singh, R. K., Vaidya, H., & Nayani, A. R. (2022). The Role of Managed ETL Platforms in Reducing Data Integration Time and Improving User Satisfaction. Journal for Research in Applied Sciences and Biotechnology, 1(1), 83–92. https://doi.org/10.55544/jrasb.1.1.12 DOI: https://doi.org/10.55544/jrasb.1.1.12

Alok Gupta. (2021). Reducing Bias in Predictive Models Serving Analytics Users: Novel Approaches and their Implications. International Journal on Recent and Innovation Trends in Computing and Communication, 9(11), 23–30. Retrieved from https://ijritcc.org/index.php/ijritcc/article/view/11108

Alok Gupta. (2024). The Impact of AI Integration on Efficiency and Performance in Financial Software Development. International Journal of Intelligent Systems and Applications in Engineering, 12(22s), 185–193. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6408

Rinkesh Gajera , "Leveraging Procore for Improved Collaboration and Communication in Multi-Stakeholder Construction Projects", International Journal of Scientific Research in Civil Engineering (IJSRCE), ISSN : 2456-6667, Volume 3, Issue 3, pp.47-51, May-June.2019 DOI: https://doi.org/10.32628/IJSRCE19338

Rinkesh Gajera , "Integrating Power Bi with Project Control Systems: Enhancing Real-Time Cost Tracking and Visualization in Construction", International Journal of Scientific Research in Civil Engineering (IJSRCE), ISSN : 2456-6667, Volume 7, Issue 5, pp.154-160, September-October.2023 DOI: https://doi.org/10.32628/IJSRCE123761

URL : https://ijsrce.com/IJSRCE123761

Rinkesh Gajera, “The Impact of Smartpm’s Ai-Driven Analytics on Predicting and Mitigating Schedule Delays in Complex Infrastructure Projects”, Int J Sci Res Sci Eng Technol, vol. 11, no. 5, pp. 116–122, Sep. 2024, Accessed: Oct. 02, 2024. [Online]. Available: https://ijsrset.com/index.php/home/article/view/IJSRSET24115101 DOI: https://doi.org/10.32628/IJSRSET24115101

Rinkesh Gajera. (2024). IMPROVING RESOURCE ALLOCATION AND LEVELING IN CONSTRUCTION PROJECTS: A COMPARATIVE STUDY OF AUTOMATED TOOLS IN PRIMAVERA P6 AND MICROSOFT PROJECT. International Journal of Communication Networks and Information Security (IJCNIS), 14(3), 409–414. Retrieved from https://ijcnis.org/index.php/ijcnis/article/view/7255

Gajera, R. (2024). Enhancing risk management in construction projects: Integrating Monte Carlo simulation with Primavera risk analysis and PowerBI dashboards. Bulletin of Pure and Applied Sciences-Zoology, 43B(2s).

Gajera, R. (2024). The role of machine learning in enhancing cost estimation accuracy: A study using historical data from project control software. Letters in High Energy Physics, 2024, 495-500.

Rinkesh Gajera. (2024). The Impact of Cloud-Based Project Control Systems on Remote Team Collaboration and Project Performance in the Post-Covid Era. International Journal of Research and Review Techniques, 3(2), 57–69. Retrieved from https://ijrrt.com/index.php/ijrrt/article/view/204

Voddi, V. K. R., & Konda, K. R. (2021). Spatial distribution and dynamics of retail stores in New York City. Webology, 18(6). Retrieved from https://www.webology.org/issue.php?volume=18&issue=60

R. Kar, V. K. Reddy Voddi, B. G. Patra and J. Pathak, "CoRL: A Cost-Responsive Learning Optimizer for Neural Networks," 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Honolulu, Oahu, HI, USA, 2023, pp. 1828-1833, doi: 10.1109/SMC53992.2023.10394113. DOI: https://doi.org/10.1109/SMC53992.2023.10394113

Narneg, S., Adedoja, T., Ayyalasomayajula, M. M. T., & Chintala, S. (2024). AI-driven decision support systems in management: Enhancing strategic planning and execution. International Journal on Recent and Innovation Trends in Computing and Communication, 12(1), 268-275. http://www.ijritcc.org

Narne, S. (2024, July 24). How data-driven strategies are revolutionizing CMS star ratings in healthcare. Forbes. https://www.forbes.com/councils/forbestechcouncil/2024/07/24/how-data-driven-strategies-are-revolutionizing-cms-star-ratings-in-healthcare/

Downloads

Published

30-06-2024

How to Cite

Srihari Padmanabhan, & Ojaswin Tharan. (2024). Effect of Marine Phycotoxins on Pediatric Neurological Health. International Journal for Research Publication and Seminar, 15(2), 295–324. https://doi.org/10.36676/jrps.v15.i2.1551