Search
191 articles for “personalization techniques”
-
Multiple Disease Prediction Using Machine Learning Algorithms
Abstract: The incorporation of machine learning algorithms into healthcare has transformed disease prediction and diagnosis. This research introduces a method for predicting various diseases using machine learning techniques. A comprehensive dataset, consisting of patient records, medical histories, and key disease-related features, was utilized to build predictive models. Data preprocessing methods, including feature selection and normalization, were implemented to clean and prepare the dataset. Several machine learning algorithms, such as Decision Trees, …
Published in Research and Reviews : A Journal of Immunology · Vol. 14, Issue 3, 2024 · pp. 34–38 Read article
-
Short Review on Indoor Farming a Future of the Country
Abstract: We are currently confronted with unstoppable tendencies in population growth, water scarcity,urbanization, and ongoing and persistent climatic change. All of these factors lead to dwindling arable land stocks per person. Land resources for agriculture are dwindling, and officials in the country are grappling with issues of sustainability and feeding the country's fast rising population. Exemplified urban vertical farming is the ideal approach for increasing food production in the future. Its …
Published in International Journal of AgroChemistry Read article
-
Implementation of Anticipating Rainfall Using Machine Learning
Abstract: Rainfall forecasting is crucial for many aspects of our national economy and should help prevent major seasonal droughts. Since agriculture is a beloved profession in many states, some Asian countries are economically hooked to decline. Previous precipitation info is beneficial. Farmers are cancerous in managing their crops, resulting in economic progress for the country. downfall prediction is hard for earth science scientists because of unordering time and unordered quantity of …
Published in International Journal of Satellite Remote Sensing · Vol. 1, Issue 1, 2023 · pp. 1–8 Read article
-
In silico Molecular Docking Analysis of Stephania glabra phytocompounds Targeting Thymidylate Kinase for potential Antituberculosis Activity
Abstract: Tuberculosis (TB) is an infectious disease caused by the bacteria Mycobacterium tuberculosis. It mainly affects the lungs and spreads through the air when a person with active TB in their lungs coughs, sneezes, or spits. This study investigates several bioactive compounds derived from plants to forecast how effective plant-based ligands will be at preventing tuberculosis. The purpose of the study was to use computational techniques to assess the effectiveness of …
Published in International Journal of Molecular Biotechnological Research · Vol. 3, Issue 2, 2025 Read article
-
Future Prospects of AI in Pharmaceutical Industry and its Limitation
Abstract: The pharmaceutical industry is facing significant challenges, including prolonged drug development timelines, high costs, and low success rates in clinical trials. Traditional methods often result in inefficiencies, with new drug development taking over a decade and billions of dollars, yet most candidates fail in clinical trials due to issues like inefficacy or safety concerns. Artificial Intelligence (AI) has become a groundbreaking technology with the potential to tackle these issues effectively. …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 2, 2025 · pp. 6–13 Read article
-
Knowledge of viral hepatitis and its prevention among college students at selected colleges of Bellary
Abstract: BACKGROUND & OBJECTIVES: Viral hepatitis is the liver disease caused by virus, the knowledge of hepatitis is essential for college students, since the students will be at risk of developing hepatitis due to their lifestyle such as sharing personal items. The aim of the study was to assess the knowledge and evaluate the effectiveness of structured teaching program on knowledge regarding viral hepatitis and its prevention among college students. METHODOLOGY: …
Published in Research and Reviews: A Journal of Medicine · Vol. 15, Issue 3, 2025 Read article
-
Advances in Biological Systems Modeling for Predicting Drug Effects in Chronic Disease
Abstract: Biological systems modeling has emerged as a promising tool for understanding and predicting the effects of drugs in the treatment of chronic diseases. Chronic diseases, such as diabetes, cardiovascular diseases, and neurodegenerative disorders pose significant challenges to traditional drug development due to their complex, multifactorial nature. Systems biology approaches, which integrate computational modeling with experimental data, provide a holistic view of disease mechanisms and treatment responses. This review explores recent …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 17–22 Read article
-
Retrieval Augmented Generation for Question Answering in Financial Documents
Abstract: In recent years, the integration of Question Answering (QA) with the Retrieval Augmented Generation (RAG) system has transformed to interact with numerous documents. It uses Natural Language Processing (NLP) techniques to improve accuracy and relevant responses derived from huge documents. RAG integrates the advantages of the retrieval and generation process, which allows systems to generate natural responses and extract context from multiple sources. The main reason to use RAG is …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 2, 2025 · pp. 62–68 Read article
-
Academia to Industry: The Impact of AI on Information Retrieval Technologies
Abstract: Artificial intelligence (AI) has significantly reshaped the field of information retrieval (IR), bridging theoretical advancements from academia with practical applications across various industries. This article explores the transformative impact of AI on IR technologies, highlighting key contributions from academic research and how they have been adapted for industry-scale implementations. Academic innovations, such as neural ranking models and semantic search techniques, have improved the accuracy and relevance of search results by …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 1, 2025 · pp. 1–7 Read article
-
Pharmaceutical Syrup Formulation Enhancing Bioavaibility and Patient Compliance
Abstract: Pharmaceutical syrup formulations are crucial for drug delivery, especially in pediatric and geriatric populations. However, challenges, such as bioavailability, stability, and patient compliance due to factors, like taste and viscosity, must be addressed. Strategies to enhance bioavailability include solubility enhancers, nanoparticle systems, and advanced techniques like solid dispersions and emulsions. Palatability plays a critical role in patient compliance, with flavoring agents, sweeteners, and texture modifications improving acceptability. Innovations, like controlled-release …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 12, Issue 1, 2025 · pp. 1–6 Read article
-
A Combined ECG and PPG Signal Powered Artificial Intelligence-Based Prediction Model for Stroke
Abstract: Stroke is one of the most common causes of morbidity and mortality around the world, and emphasis on prevention and early detection strategies cannot be overstated. This review aims to integrate techniques of artificial intelligence with electrocardiogram and photoplethysmogram signals to enhance stroke prediction and monitoring of cardiovascular health. All in all, the application of artificial intelligence that incorporates machine learning, deep learning, or hybrid models gives robust tools toward …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 2, 2025 · pp. 18–26 Read article
-
Smart Framework for Personal Fuel Expense Tracking and Carbon Emission Assessment
Abstract: This study presents a smart system that is intended to assist individuals and administrators in tracking their fuel costs and keeping an eye on their daily carbon emissions. It makes it simpler to make decisions by examining fuel consumption and its effects on the environment. The technology gathers real-time emissions data from vehicles equipped with Internet of Things devices. It can predict future trends of emissions by utilizing AI-based predictive …
Published in Journal of Thermal Engineering and Applications · Vol. 11, Issue 3, 2024 · pp. 36–44 Read article
-
Ayurveda as a Medium of Healing: A Critical Review of Classical Concepts and Modern Evidence
Abstract: Ayurveda, recognized as one of the world’s oldest holistic healing systems, has its origins in India over 5,000 years ago. Rooted in a philosophy that views health as a harmonious balance of body, mind, and spirit, Ayurveda offers a comprehensive and individualized approach to wellness. This traditional system of medicine is grounded in the concept of the Tridosha Vata, Pitta, and Kapha representing the fundamental bio-energetic forces governing physiological and …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 14, Issue 3, 2025 · pp. 40–44 Read article
-
AI-Based Early Diagnosis & Prevention of Diabetes
Abstract: The worldwide burden of Diabetes Mellitus, especially Type 2 diabetes (T2D) has escalated to a critical level. Early detection of diabetes is essential to reduce long‑term complications and healthcare costs. This study explores the use of artificial intelligence (AI) techniques to improve the early diagnosis and prevention of diabetes. We developed an AI model using the Random Forest algorithm, the model predicts diabetes risk based on clinical and lifestyle variables …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
-
Computational Approaches to Understanding Cellular Signaling Pathways
Abstract: Cellular signaling pathways are fundamental in regulating vital processes, such as cell growth, differentiation, and apoptosis. The intricate and interconnected nature of these signaling networks requires sophisticated methods for their analysis. Computational approaches, including mathematical modeling, network analysis, and machine learning, have revolutionized the way researchers analyze and simulate cellular signaling. This article provides a comprehensive overview of computational strategies employed to model signaling pathways, with a focus on integrating …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 8–13 Read article
-
Association Rule Mining for Predicting Heart Disease: Challenges and Opportunities
Abstract: The exponential growth of digital healthcare data has spurred innovative applications of data mining techniques in medical research and practice. Among these, association rule mining stands out for its ability to uncover meaningful correlations within diverse datasets, such as electronic health records, imaging data, and genetic information. This paper reviews the application of association rule mining in predicting heart diseases, emphasizing its potential to enhance early detection, risk stratification, and …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 3, 2024 · pp. 29–34 Read article
-
Aura Pulse: An AI-Powered System for Real-Time Emotional Support and Personalized Recommendations
Abstract: Aura Pulse is a cutting-edge AI-powered platform developed to provide real-time emotional support, tackling the growing challenges of stress, anxiety, and burnout in today’s fast-moving digital era. Utilizing advanced facial expression analysis, Aura Pulse interprets visual cues to create a comprehensive emotional profile of the user. This instant emotional evaluation enables the platform to deliver personalized suggestions aligned with the user’s mood and mental state, promoting overall well- being and …
Published in Journal of Advancements in Robotics · Vol. 13, Issue 1, 2026 · pp. 18–25 Read article
-
Enhancing Library Engagement: A Student-Centric Study at MDSD College, Ambala City
Abstract: The primary objective of this study is to examine the patterns of library usage, reading habits, motivational drivers, and the barriers that influence students’ engagement with library services at MDSD College, Ambala City. The research aims to identify both enabling and inhibiting factors to enhance the effectiveness of library resources and promote a vibrant reading culture. A quantitative research design was employed using a structured questionnaire distributed to a sample …
Published in Journal of Advancements in Library Sciences · Vol. 13, Issue 1, 2026 · pp. 15–27 Read article
-
Advanced Techniques in Filler Layering for the Malar Region: Implications for Cellular Integrity and Long-Term Outcomes
Abstract: Objective: This review investigates advanced filler layering techniques for the malar region, focusing on cellular integration, collagen remodeling, hydration dynamics via aquaporin channels, genetic responses, and filler performance over time. Emphasis is placed on high-density HA fillers (Lyft, Voluma, Volift, and Volux), examining cellular-level mechanisms, genetic interactions, and the role of key pathways (TGF-β, ERK/MAPK, AQP3) in long-term outcomes. Methods: A systematic review was conducted, focusing on genetic, cellular, and …
Published in International Journal of Biochemistry and Biomolecule Research · Vol. 3, Issue 1, 2025 · pp. 10–19 Read article
-
Comparative Assessment of Methylparaben concentration in Cosmetic product, analyzed using Enzyme Biosensor and ultra-high-pressure liquid chromatography (UPLC): An approach towards detection of the environmental toxicant with higher accuracy and sensitivity.
Abstract: Methylparaben (MP) is one of the most widely used preservatives and is associated with a catalog of recently identified health hazards. Existing studies have also highlighted these compounds as environmental contaminants and toxicants that affect water quality and the associated microbial diversity of the habitat. The conventional methods for parabens detection is performed using chromatographic techniques, which assist in quantitative analysis of the group of compounds. However, the biggest challenge …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 2, 2025 Read article