A HYBRID MACHINE LEARNING AND DEEP LEARNING ARCHITECTURE FOR AUTOMATED MEDICAL DIAGNOSIS USING HIGH-DIMENSIONAL CLINICAL AND BIOMEDICAL DATA
The speed of the electronic healthcare system, clinical information system, and biomedical sensing technologies has resulted in the creation of extremely huge high-dimensional and heterogeneous medical data. Such data have substantial potential to automatically diagnose diseases, but are difficult to use because they are feature redundant, nonlinea...
By Komal Saxena, M. Praneesh, S. Nancy Lima Christy, K. Nandhini, Tolib Rajabov, M. Nalini, Shalu Gupta
AN ADVANCED MULTIMODAL AI FRAMEWORK FOR EARLY BRAIN STROKE DETECTION USING HYBRID FEATURE SELECTION, ENSEMBLE MODELS, AND REINFORCEMENT LEARNING
The detection of stroke is vital since any delay in diagnosis may lead to significant disability or the loss of life. The existing predictive models fail to capture stroke symptoms with accuracy because of low complexity, and the ability to be used in the real-time situation in the clinical setting. In the following paper, an AI-based system of ear...
By D. Ushasree, A.V. Praveen Krishna, Ch. Mallikarjuna Rao, D.V. Lalita Parameswari
EXPLORING THE IMPACT OF INNOVATION ON INDIA'S SCIENTIFIC EQUIPMENT INDUSTRY THROUGH GLOBAL PARTNERSHIPS
The paper discusses the importance of innovation in revolutionizing the scientific equipment market in India with a lot of focus on how it has changed supplier firms and its end consumers particularly the pharmaceutical industry. It underscores the use of new technologies and models of business with regard to improved operational performance and ef...
By Dinakar Lingam, Syed Jaffer
DESIGN AND IMPLEMENTATION OF AN AI-BASED MEDICAL ANALYTICS FRAMEWORK EMPLOYING DEEP NEURAL NETWORKS AND ADVANCED MACHINE LEARNING MODELS FOR PRECISION HEALTHCARE
The digitalization of healthcare is fast, bringing about abundant and diverse medical data with novel opportunities to bring precise healthcare with the help of artificial intelligence (AI) associated analytics. Traditional methods of data analysis in medical fields frequently do not describe nonlinear and complex relationships in multimodal clinic...
By B. Senthilkumaran, Gajraj Singh, Ali Bostani, S. Krithika
ARTIFICIAL INTELLIGENCE–EMPOWERED DIGITAL TWINS FOR SIMULATION-DRIVEN SECURITY, PRIVACY, AND RESILIENCY OPTIMIZATION IN 6G NETWORKS
The wireless networks of the sixth generation (6G) are likely to be an AI-native, highly dynamic, and ultra-dense communication eco-system, where the question of security, privacy and resiliency is much more complicated to address than in other generations. Conventional static and prescriptive network management tools cannot scale, be heterogeneous...
By P. Senthilkumar
NEUROMORPHIC-INSPIRED HYBRID COGNITIVE MODEL FOR SELF-OPTIMIZING RESOURCE MANAGEMENT IN 6G EDGE NETWORKS
Introduction: The 6G world requires connected intelligence, but there is a crucial paradox between the standards of Large Language Model (LLM) and edge constraints. The premium devices have up to 6-12GB of DRAM, whereas the typical 175B models need 350GB of storage, which is 30 times that of the premium version. Literature Survey: It has been...
AN AI-DRIVEN DIGITAL TWIN FRAMEWORK LEVERAGING ONTOLOGIES, INTELLIGENT DATA MANAGEMENT, AND SIMULATION FOR SECURITY AND RESILIENCE IN 6G NETWORKS
The 6G wireless networks will be used in autonomous systems, extended reality, digital healthcare, and large-scale cyber-physical infrastructures, making it possible to provide applications they previously did not know to be intelligent and ultra-reliable communication. Nevertheless, 6G networks are quite complicated and heterogeneous, which are ch...
By P. Karunakaran1, Ali Bostani, Salomov Gulom, S. Shantha Kumar, V. Manimala, T. Velmurugan, R. Praveenkumar
EDUCATIONAL FOUNDATIONS OF AGRICULTURAL TECHNOLOGIES AND THEIR INFLUENCE ON PRECISION AGRICULTURE AND SUSTAINABILITY PRACTICES
Even though agriculture is now one of the most technologically advanced civilian industries, there is still a big gap between the innovations that are available and how they are actually put into practice, particularly in areas where traditional supervision methods are predominant. This study looks at how farmers' ability to implement precision agr...
By Shoira Bobomuratova, Kurbonalijon Zokirov, Najimiddin Jumakulov, G'ofur Allamuratov, Oybek Ulugbekov, Muhabbat Mullajonova, Avazbek Turdunov
AN ECOLOGICAL FRAMEWORK OF STUDENT RESILIENCE IN THE POST-PANDEMIC CONTEXT
The paper examines the impact of online communities, learning environment, family harmony, and health habits, and their effects on student resilience and work-life balance in post-pandemic Kerala. It also studies the mediation effect of resilience between these factors and academic adaptability, as well as well-being. A mixed-method sequential desi...
By Bobby Pudukaden, A. Martin Jayaraj
GEOTECHNICAL APPROACHES FOR BUILDING EARTHQUAKE-RESILIENT INFRASTRUCTURE IN URBAN ENVIRONMENTS
The seismic nature of the soil in urban spheres is very susceptible to seismic ground failures caused by intricate soil conditions, extensive development, and outdated construction methods. However, structural solutions have always played the most important role in seismic design; growing evidence points to the importance of geotechnical engineerin...
By Jainish Roy, Rajesh Sehgal