Category Archives: Uncategorized

Authors: Prabhakar Tripathi, Amit Thakur

Abstract: Engaging in physical activity and exercise is essential for maintaining a healthy lifestyle and is a key factor in preventing and enhancing health. However, certain sports and physical activities may present an inherent risk of injury. Some intrinsic, extrinsic, mutable, non-mutable and initiating events may contribute as causes of injury in sports. This thematic review will provide an overview of the mechanisms that lead to sports injuries and the various elements that influence them. It will also explore the effects of sports injuries, how technology and innovation can be used to manage these risks and injuries, the significance of early risk analysis, and finally, future trends and directions in artificial intelligence research to reduce the risk of sports injuries and the strategies for managing them. By amalgamating the current state of knowledge within this field, the author aims to enhance our comprehension of the complex interplay and intricate relationship between the mechanisms of sports injuries and the prevention, management, and treatment of such injuries using emerging and evolving technologies. It's essential to emphasize and underscore that advanced technologies should be seen as a complement and augmenting the role of healthcare professionals rather than substituting them, given the recognized limitations of the current system and the imperative necessity for personalized and tailored treatments that can vary from one athlete to another.

 

 

Published by: vikaspatanker

Authors: Nilesh Shrivas, Amit Thakur

Abstract: The development of artificial intelligence (AI) based medical Internet of Things (IoT) technology plays a crucial role in making the collection and exchange of medical information more convenient. However, security, privacy, and efficiency issues during information exchange have become pressing challenges. While many scholars have proposed solutions based on AI and blockchain to address these issues, few have focused on the impact of the slow consensus algorithm of blockchain on the efficiency of information exchange. To improve the efficiency of information exchange, we propose an information exchange approach based on AI and DA Genabled blockchain, providing a secure and efficient environment for information exchange in the medical IoT. Additionally, to enhance the efficiency of information exchange in the medical IoT, a novel tip selection algorithm is introduced to reduce the time delay in reaching consensus, thereby enabling faster acquisition of trusted information via blockchain. Simulation results demonstrate that compared to methods based on traditional DAG-enabled blockchain, the approach proposed in this paper improves the efficiency of information exchange.

 

 

Published by: vikaspatanker

Authors: Francis Mumba

Abstract: Exploring The Difficulties And Prospects Brought With The Adoption Of Computer Studies In Public Learning Institutions: A Case Study Of Four Selected Public Day Secondary Schools In Luwingu District Of Northern Province, Zambia

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Published by: vikaspatanker

Authors: Vaishnavi Yelnare, Dr.Santosh Gaikwad, Dr. A. A. Khan, Dr. R. S. Deshpandes

Abstract: This research undertakes an in-depth exploration into the utilization of machine learning algorithms for the recognition and classification of sign languages commonly used by individuals within the deaf and mute communities. We evaluate different models, such as CNNs, LSTMs, and hybrid networks, for gesture recogni- tion, image processing, and sequence classification. Chal- lenges including lighting, occlusion, inter-user variability, and data scarcity are addressed. Experiments are con- ducted on real-world datasets like RWTH-BOSTON and American Sign Language (ASL) to benchmark model performance. Our study contributes a scalable, real-time framework for sign language recognition, which aids in bridging communication gaps for the hearing-impaired community.

 

 

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Rakesh. S A
Affilation:	Assistant Professor Department of Pharmacognosy GM Institute of Pharmaceutical Sciences and Research, Davanagere 577006, Karnataka, India
Email-Id:	rakesh@gmipsr.ac.in
Publication: “Pharmacognostic evaluation of triphala herbs and establishment of chemical stability of triphala caplets”, International Journal of Pharmaceutical sciences and Research, Vol (7), Jan 2016, 1000-09. “Development and validation of a RP-HPLC method for quantitative analysis of Piperine and chemical standardization of piper nigrum L”. International Journal of Advanced scientific Research and publications (IJASRP). Pharmaceutical Vol (3), page no 11-16(Jan 2017). “Unveiling the Bioactive Potential of Lantana camara in Relation to its Anti-oxidant and Antimycotic Properties”. RJPS 2024;14(3):15-21.

 

Published by: vikaspatanker

Authors: Nagendra Kumar, Manjesh Gowda

Abstract: Clinical trials are fundamental to the development of new drugs and therapies, but they are also notoriously time-consuming, expensive, and complex. With traditional processes often taking more than a decade and costing billions, there is a growing need for innovation to make clinical trials more efficient and cost-effective. Artificial Intelligence (AI) offers transformative solutions by automating data analysis, optimizing patient recruitment, improving trial design, and enabling real-time monitoring. This paper explores how AI is revolutionizing clinical trial processes, significantly reducing time and cost while improving accuracy and patient outcomes. It also examines challenges in implementation, regulatory concerns, and future prospects. By integrating AI into the clinical trial lifecycle, pharmaceutical companies, contract research organizations (CROs), and healthcare providers can accelerate drug development and deliver safer, more effective therapies to market.

DOI: http://doi.org/10.61137/ijsret.vol.8.issue6.568

 

 

Published by: vikaspatanker

Authors: Shailesh Yadav

Abstract: Personalized medicine, which tailors medical treatment to individual patient characteristics, has been significantly enhanced by advances in artificial intelligence (AI). AI enables the integration and analysis of vast amounts of patient data, facilitating precise diagnostics and personalized therapeutic interventions. The adoption of AI in personalized medicine is reshaping traditional healthcare business models by introducing new value creation mechanisms, revenue streams, and stakeholder dynamics. This paper explores the evolving business models that support AI-enabled personalized medicine, focusing on value propositions, revenue generation, partnerships, and challenges in commercialization. The analysis highlights how innovative business frameworks are essential to translating AI technologies into sustainable healthcare solutions that improve patient outcomes and deliver economic value. Strategic implications for startups, established healthcare providers, and payers are discussed, alongside considerations for regulatory environments and ethical dimensions. The paper concludes by outlining future trends and opportunities for business innovation in AI-driven personalized healthcare.

DOI: http://doi.org/10.61137/ijsret.vol.8.issue6.567

 

 

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Authors: Sumanth Sai Krishna

Abstract: Artificial intelligence (AI) has revolutionized healthcare diagnostics by enabling faster, more accurate, and often less invasive disease detection. As AI-driven diagnostic tools become increasingly prevalent, assessing their economic impact is essential for healthcare providers, payers, and policymakers. This paper provides a comprehensive economic evaluation of AI diagnostic technologies, focusing on cost-effectiveness, budget impact, and value-based healthcare implications. It examines how AI tools influence healthcare costs, patient outcomes, workflow efficiencies, and access to care. Methodological approaches for economic evaluations, challenges in data collection and analysis, and case studies of successful AI diagnostic implementations are discussed. The paper also explores the broader systemic effects of AI diagnostics on healthcare delivery models, reimbursement strategies, and long-term sustainability. Ultimately, this evaluation underscores the potential for AI-driven diagnostics to deliver economic value while improving clinical outcomes and patient experiences.

DOI: http://doi.org/10.61137/ijsret.vol.8.issue6.566

 

 

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Authors: Naresh Kumar

Abstract: Artificial intelligence (AI) is reshaping drug development pipelines across the pharmaceutical industry, driving innovation, reducing costs, and shortening time-to-market for new therapies. This paper analyzes the impact of AI from a business perspective, focusing on how pharmaceutical companies and biotech startups leverage AI technologies to optimize discovery, preclinical research, clinical trials, and regulatory processes. The integration of AI not only enhances scientific outcomes but also transforms business models, investment strategies, and competitive dynamics. Challenges such as data governance, regulatory compliance, and workforce adaptation are discussed alongside strategic recommendations for successful AI adoption. This comprehensive analysis highlights how AI-enabled drug development can provide sustainable business value, foster industry disruption, and ultimately improve patient care worldwide.

DOI: http://doi.org/10.61137/ijsret.vol.8.issue6.565

 

 

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Authors: Professor Amit Thakur, Tanishka Mangal

Abstract: Clustering in wireless sensor network (WSN) is an efficient approach to provide prolonged network life time, scalability and data aggregation. Clustering also conserves the limited energy resources, for this reason in this work; we propose an energy aware static clustering routing protocol for WSN. The specificity of this work is that the network is partitioned into static clusters that contain a Primary Cluster Head (P-CH) and a Secondary Cluster Head (S-CH) and both of them are selected based on energy. The simulation results show that the new protocol proposed in this work extends the network lifetime and balances the energy consumption of the network nodes.

Published by: vikaspatanker