Authors: Dr. Ashwin Kumar

Abstract: Artificial Intelligence (AI) is revolutionizing clinical trial participant recruitment by automating and optimizing key processes such as eligibility screening, patient matching, and engagement. Traditional recruitment methods face challenges including time-consuming manual efforts, low enrollment rates, and demographic disparities, which delay trials and increase costs. AI technologies—such as machine learning, natural language processing, predictive analytics, and chatbots—enable efficient analysis of complex patient data from electronic health records and other sources, improving recruitment speed, accuracy, and inclusivity. While AI-driven recruitment offers significant benefits like reduced timelines, enhanced patient retention, and cost savings, it also raises ethical and regulatory concerns including data privacy, algorithmic bias, and transparency. Future developments integrating real-world data, explainable AI, and digital health platforms promise to further advance recruitment practices. This article reviews the current applications, benefits, challenges, and future directions of AI in clinical trial participant recruitment, highlighting its potential to transform clinical research and accelerate medical innovation.

DOI: http://doi.org/10.61137/ijsret.vol.11.issue3.128

 

 

Published by: vikaspatanker

Authors: Dr. Harika Prasad

Abstract: AI technologies are transforming medication adherence by enabling personalized, real-time interventions that address the complex factors influencing patients’ ability to follow prescribed regimens. By leveraging machine learning, predictive modeling, natural language processing, and data integration from diverse sources—including electronic health records, wearable devices, and patient-reported outcomes—AI systems can monitor adherence patterns, predict patients at risk of non-compliance, and deliver tailored reminders and support through virtual health coaches and chatbots. These innovations improve patient engagement, facilitate early intervention, and empower healthcare providers with actionable insights, ultimately enhancing treatment outcomes and reducing healthcare costs. However, successful implementation requires careful consideration of ethical, privacy, and regulatory challenges to ensure fairness, transparency, and patient trust. As AI continues to evolve, its integration into medication adherence management promises to revolutionize personalized care, offering scalable solutions that improve quality of life for millions worldwide.

DOI: http://doi.org/10.61137/ijsret.vol.11.issue3.127

 

 

Published by: vikaspatanker

Authors: Vishal Garad, Dr. Quazi khabeer, Dr. A. A. Khan, Dr. R. S. Deshpande

 

 

Abstract: Cloud computing has transformed the business and industry operations by providing scalable, flexible, and cost- efficient data storage, processing, and access solutions.The paper discusses the revolutionary effects of cloud computing on business processes and its benefits, challenges, and future trends. It identifies the contributions of cloud technologies to enhanced operational efficiency, innovation, and sustainable practices.Index Terms—Cloud Computing, Scalability, Operational Efficiency, Security, Cost-Effectiveness, Future Trends.

DOI: http://doi.org/

 

 

Published by: vikaspatanker

Authors: Assistant Professor DR. Ritu Jain, Aditya Pratap Saroj

Abstract: The Himalayan glaciers, also referred to as the "Third Pole," play a vital role in the ecological balance of the region and supply water to more than a billion Asians, sustaining agriculture, drinking water, and energy. Climate change has resulted in rapid glacial retreat, which has resulted in decreased water resources, enhanced disaster risks, and ecosystem threats. This chapter examines the effect of glacial melt, employing remote sensing, satellite imagery, and climate models to evaluate the scale of retreat and its consequences, including water scarcity and ecosystem disruption. It discusses adaptive measures, such as enhanced water storage, flood early warning systems, and sustainable agriculture to reduce the impacts of declining glacial melt. Community-based techniques, combining indigenous knowledge, are also mentioned as important in controlling water resources. Lastly, the chapter discusses the necessity of cross-border policy and cooperation to develop solutions for the water crisis to ensure the sustainable management of the region's glaciers and water.

 

 

Published by: vikaspatanker

Authors: Assistant Professor Dr. Ritu Jain, Kajal Pandey

Abstract: Urban sprawl, defined as the haphazard expansion of city boundaries into rural and peri-urban lands, is a defining characteristic of contemporary urban growth in India. As a prominent Tier-2 city and capital of Uttar Pradesh, Lucknow has witnessed accelerated sprawl patterns over the past three decades. This paper investigates the extent, causes, and implications of this urban expansion using remote sensing data, GIS techniques, demographic trends, and field-based insights. With a focus on infrastructure strain, socio-economic disparities, environmental degradation, and spatial policy inefficiencies, this research identifies key trends, challenges, and solutions. Recommendations are proposed for integrated planning, sustainable growth, and data-driven governance.

 

 

Published by: vikaspatanker

Authors: Pallavi Srivastava

Abstract: In low-resource environments, diagnostic tools must prioritize affordability while also delivering accuracy, reliability, and durability suited to the unique challenges of the developing world. In recent years, global health diagnostics using minimally instrumented, microfluidic platforms with low-cost disposable components have gained momentum, driven in part by funding from organizations like the Bill & Melinda Gates Foundation and the National Institutes of Health. This surge in interest has resulted in a variety of promising prototype devices, many of which are undergoing advanced development or clinical testing. These include systems capable of multiplexed PCR assays targeting enteric, febrile, and reproductive tract infections, as well as immunoassays for conditions like malaria, HIV, and sexually transmitted infections. More recent innovations feature fully disposable diagnostics that operate without instruments, utilizing isothermal nucleic acid amplification techniques. Despite these advancements, scalable and truly low-cost manufacturing methods remain a major hurdle in creating affordable diagnostic solutions at volume. This overview highlights current platform development efforts, includes original research conducted at PATH, and emphasizes the need for continued action and innovation in this field.

 

 

 

Published by: vikaspatanker

Authors: Assistant Professor Dr. Ritu Jain, Himanshu Kasaudhan

Abstract: The Northeastern region of India, comprising the states of Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim, and Tripura, represents a critical ecological zone within the Indo-Burma biodiversity hotspot. This area is home to a vast range of endemic and threatened species and features one of the highest levels of biological diversity in India. However, rapid deforestation caused by anthropogenic pressures—such as shifting cultivation (jhum), illegal logging, infrastructure expansion, and population growth—has led to severe ecological degradation. This chapter explores how Remote Sensing (RS) and Geographic Information Systems (GIS) have been employed to monitor forest cover changes and assess their impact on biodiversity. Through the use of satellite imagery, spatial analysis, biodiversity indices, and ecological modeling, this study highlights the extent, patterns, and consequences of deforestation on flora and fauna. The chapter concludes by offering conservation strategies and policy recommendations grounded in geospatial data and ecological science.

 

 

 

Published by: vikaspatanker

Authors: Assistant Professor Benasir Begam.F, Assistant Professor Agalya.A, Assistant Professor Gopalakrishnan T

Abstract: Machine vision, a sub-discipline of computer science and artificial intelligence, has evolved into a robust technological framework that enables machines to interpret and make decisions based on visual data. This review delves into the computational underpinnings of machine vision, tracing its development from classical image processing techniques to state-of-the-art deep learning architectures. Special emphasis is placed on domain-specific applications such as autonomous navigation, medical diagnostics, and smart manufacturing, highlighting how vision-enabled machines are reshaping real-world operations. The paper further explores benchmark datasets, evaluates key performance metrics, and outlines critical challenges. It concludes with a forecast of emerging paradigms—such as transformer-based vision models and neuromorphic computing—that promise to redefine the future of intelligent visual systems.

 

 

Published by: vikaspatanker

Authors: R.Aswathi, Dr.Karthikeyan S, K.Mehar Banu, Dr.Manimegalai R M.

 

 

Abstract: The platform’s intuitive user interface is designed for ease of use by This paper presents the design and development of a Digital Log Website tailored for biotechnology laboratories, aimed at enhancing the accuracy, efficiency, and compliance of scientific data documentation. In many research and clinical environments, traditional paper-based lab notebooks remain the norm, despite being prone to a variety of issues including data loss, transcription errors, lack of standardization, and limited accessibility across teams. These limitations pose significant challenges for reproducibility, collaboration, and regulatory compliance. The proposed digital log system offers a centralized, web-based platform that addresses these challenges by enabling real-time data entry, seamless integration with laboratory instruments, and streamlined communication among team members. Built using modern cloud technologies, the system supports scalability, remote access, and automated backups, ensuring data integrity and availability. Key features include secure user authentication, role-based access control, version tracking, and comprehensive audit trails to meet regulatory standards such as FDA 21 CFR Part 11 and GLP requirements. Students and lab technicians, minimizing training time while maximizing productivity. By transitioning from paper to digital documentation, laboratories can significantly improve data about instrument , reduce data loss risks, and enhance overall record quality and compliance readiness.

DOI: http://doi.org/

 

 

Published by: vikaspatanker

Authors: Research Scholar Aman Malik

Abstract: The proliferation of cloud computing has revolutionized data storage, access, and management, but it has also introduced complex challenges concerning cross-border data flow and legal jurisdiction. As data transcends national borders, existing legal frameworks struggle to keep pace with the decentralized nature of cloud services. This paper examines the legal, technological, and regulatory implications of cross-border data flows within cloud infrastructures, emphasizing the tension between data sovereignty and global commerce. The study explores how different jurisdictions—particularly the European Union with the General Data Protection Regulation (GDPR), the United States with its sectoral approach, and emerging frameworks in Asia—address data localization, transfer mechanisms, and enforcement of jurisdiction. Through a comparative legal analysis, the paper highlights gaps, overlaps, and potential conflicts in international data regulation. It concludes with recommendations for harmonized legal standards, multilateral cooperation, and technologically adaptive policies to ensure secure, compliant, and innovation-friendly data ecosystems.

 

 

Published by: vikaspatanker