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103 articles for “prediction”
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ML Analysis of Factors Affecting Vaccination in Rural Children: A Machine Learning Approach
Abstract: Vaccination remains one of the most effective public health interventions for preventing childhood diseases, yet rural regions in India continue to experience uneven immunization coverage due to multiple socioeconomic and geographic barriers. This research applies machine learning techniques to identify and analyze the major determinants influencing childhood vaccination uptake in rural communities. The study utilizes survey-based demographic, socioeconomic, and healthcare-related parameters to build predictive models that classify children as vaccinated …
Published in International Journal of Vaccines · Vol. 3, Issue 2, 2026 Read article
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NeoVax: Smart Child Vaccination and Monitoring Platform
Abstract: Child vaccination plays a crucial role in preventing life-threatening diseases and ensuring long-term public health. Despite the availability of structured immunization programs, many children miss scheduled vaccinations due to lack of awareness, busy lifestyles of parents and absence of effective reminder systems. This research paper presents NeoVax, a smart and user-friendly child vaccination reminder and management system designed to address these challenges using digital technology.NeoVax is an Application that enables …
Published in International Journal of Children · Vol. 3, Issue 2, 2026 · pp. 14–20 Read article
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Striking A Balance: Ethical Guidelines for A.I. Integration in Mental Health Services
Abstract: Introduction: Artificial Intelligence (AI) integration in mental health services presents opportunities and challenges. This study examines ethical considerations and proposes guidelines for responsible AI implementation in mental healthcare. The rapid advancement of AI technologies has sparked both excitement and concern within the mental health community, necessitating a thorough examination of their potential benefits and risks. By addressing these ethical considerations, this research aims to contribute to the development of a …
Published in International Journal of Behavioral Sciences · Vol. 2, Issue 1, 2025 · pp. 8–15 Read article
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Data-driven Approaches to Mineral Resource Management Using AI: A Brief Review
Abstract: The role of Artificial Intelligence (AI) in the mineral resource sector has become increasingly significant over the past few years, as industries seek to optimize and modernize their operations. AI encompasses a variety of technologies and techniques, such as machine learning, deep learning, and expert systems, that are now widely used in mineral exploration, resource estimation, and mine management. These AI-driven approaches have brought about a transformative shift, enhancing efficiency, …
Published in International Journal of Minerals · Vol. 2, Issue 1, 2025 · pp. 25–29 Read article
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A Decade of Viral Evolution (2015–2025): Emergence, Mutations, and Implications for Global Health
Abstract: Over the past decade (2015-2025), viral evolution has profoundly reshaped the global health landscape, challenging healthcare systems, diagnostic tools, therapeutic strategies, and vaccine efficacy. This review comprehensively analyzes the evolutionary trajectories of major human and zoonotic viruses, with a focus on pandemic-prone, drug-resistant, and emerging pathogens. Viral evolution is driven by diverse molecular mechanisms including high mutation rates, recombination, reassortment, host immune pressure, and antiviral interventions, leading to genetic diversification, …
Published in International Journal of Vaccines · Vol. 2, Issue 2, 2025 · pp. 31–40 Read article
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A Study on accelerating threat of Emerging Infectious Diseases (EIDs) and imperative for a proactive, interdisciplinary Global Health Security Framework
Abstract: Emerging Infectious Diseases (EIDs) represent one of the most critical and persistent threats to global health security in the 21st century. Driven primarily by the synergy of unprecedented human encroachment into wild habitats, climate change-induced ecological disruption, accelerated international travel, and antimicrobial resistance, the frequency and severity of zoonotic spillover events are rapidly increasing. Traditional, reactive public health measures—focused on containment after an emergence—have repeatedly proven insufficient, leading to catastrophic …
Published in International Journal of Tropical Medicines · Vol. 3, Issue 1, 2026 · pp. 8–21 Read article
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Machine Learning for Finding Materials for Membranes
Abstract: Traditionally, finding and improving membrane materials has depended on trial-and-error experiments, which can take a long time, cost a lot of money, and only cover a small area. Recent improvements in machine learning (ML) have the potential to change the way membrane materials are designed by making it possible to make predictions about performance, selectivity, and stability based on data. ML algorithms can find hidden links between the structure, composition, …
Published in International Journal of Membranes · Vol. 3, Issue 1, 2026 · pp. 1–7 Read article
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The Influence of Data Analytics on Sports Performance
Abstract: Data analytics has drastically changed how we evaluate, improve, and maintain athletic performance. Coaches used to use subjective observations as well as only limited numbers of statistics to consider player performance; however, tracking technology is now advancing at a fast pace. There are now very large amounts of real-time data available on athletes in regards to speed, movement patterns, fatigue, efficiency, etc. This enables all teams to more accurately make …
Published in Recent Trends in Sports · Vol. 3, Issue 1, 2026 · pp. 15–21 Read article
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Student Academic Achievement Forecast Based on Emotional Intelligence, Personality, Demographic Characteristics and Attitude Towards Education and Future Career
Abstract: This study was aimed at predicting students' academic achievement based on emotional intelligence of personality traits, attitudes to education and future career. The present study was a correlational-analytical study. The statistical population of Zanjan University students in the academic year of 1395-1395 was the sample of 489 people selected by cluster random sampling method. Academic Resilience Scale (ARI) and Schotte Emotional Intelligence Questionnaire and Researcher Attitude Questionnaire were used to …
Published in International Journal of Education Sciences · Vol. 1, Issue 2, 2024 · pp. 25–36 Read article
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Integrating Atmospheric Science: Understanding Greenhouse Gases, Aerosols, and Air Quality Dynamics
Abstract: Atmospheric science investigates the Earth’s atmospheric systems to understand their composition, dynamics, and the implications for climate, weather, and air quality. This review explores five primary areas within the field: atmospheric composition, atmospheric modeling, remote sensing, air pollution, and boundary layer dynamics, highlighting critical challenges and advancements. Rising levels of greenhouse gases (GHGs), including carbon dioxide and methane, continue to drive global warming, while feedback mechanisms—like cloud interactions and surface …
Published in International Journal of Atmosphere · Vol. 1, Issue 1, 2024 · pp. 32–35 Read article
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InSilico Analysis and Homology Modeling of Tetrahydroprotoberberine Oxide involved in the Berberine Biosynthesis
Abstract: Objective: Berberine, a bioactive compound found in various plant species, exhibits diverse pharmacological properties with potential applications in pharmaceutical research. The biosynthesis of berberine involves several enzymatic steps, with (S)-tetrahydroprotoberberine oxidase playing a pivotal role. This study aimed to elucidate the structural and functional characteristics of (S)-tetrahydroprotoberberine oxidase to better understand its role in berberine biosynthesis and its potential biotechnological applications. Methods: Using bioinformatics tools and computational methods, the physicochemical …
Published in Emerging Trends in Metabolites · Vol. 1, Issue 1, 2024 · pp. 7–26 Read article
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AI For Climate Vulnerability Assessment
Abstract: Climate change is one of the biggest problems we face every day. The main problems are high temperatures, rising sea levels, and changes in weather, which will be worse in the upcoming years. To predict and adapt to these impacts, we need to create data-driven solutions. The main tool for predicting climate change was artificial intelligence, which can also be utilised to predict the weather and alert people of impending …
Published in International Journal of Radio Frequency Innovations · Vol. 3, Issue 1, 2025 · pp. 18–33 Read article
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The Influence of Self-Efficacy on Anxiety and Perfectionism among Dancers
Abstract: The world of dance, while driven by creativity, often imposes significant psychological demands on performers. This study explored how self-efficacy influences anxiety and perfectionism—both adaptive (excellencism) and maladaptive—among dancers, with a focus on gender differences. A sample of 120 dancers (60 males, 60 females) was assessed using standardized scales. Relationships and predictive effects were assessed using statistical techniques, such as regression, Pearson correlation, and t-tests. Findings revealed no significant gender …
Published in International Journal of Behavioral Sciences · Vol. 2, Issue 2, 2025 Read article
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Progression of Health and Wellness: Artificial Intelligence (AI) and Deep Learning (DL) for Precision Medicines
Abstract: Deep learning and artificial intelligence in the field of precision medicine is revolutionizing healthcare to make personalized therapeutic approaches desirable based on the unique characteristics of the patient. AI technologies improve diagnostic accuracy by analyzing medical data, spotting patterns and anomalies that human experts may miss. AI-driven models are instrumental in precision medicine, where they can predict patient response to therapies to tailor treatment plans, enhancing outcomes and reducing adverse …
Published in Emerging Trends in Personalized Medicines · Vol. 2, Issue 2, 2025 · pp. 1–5 Read article
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The Influence of Self-Efficacy on Anxiety and Perfectionism among Dancers
Abstract: The world of dance, though celebrated for its creativity and artistic freedom, often carries considerable psychological demands on performers. Beyond the physical rigor, dancers navigate pressures of performance standards, audience expectations, and internalized goals of perfection. This study examined how self-efficacy—an individual’s belief in their own capability—shapes the experiences of anxiety and perfectionism among dancers, with a particular focus on gender differences. A balanced sample of 120 dancers (60 males …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 37–44 Read article
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Forecasting Climate-Driven Healthcare Demand in Agricultural Regions: A Multi-Modal AI Approach
Abstract: The rapidly increasing instability of world climatic regimes has made past meteorological thresholds irrelevant, especially in the agricultural areas where monetary stability and well-being of humans are closely intertwined with an environmental situation. The more the frequency of 1 in every 1000-year events, i.e., heatwaves and catastrophic flooding increase, the greater the rural healthcare systems are in crisis, i.e., unable to predict a surge in demand because of data scarcity, …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 28–38 Read article
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Explainable Artificial Intelligence in Personalized Medicine: Emerging Clinical Perspectives
Abstract: The convergence of artificial intelligence (AI) and precision medicine has transformed contemporary healthcare by enabling data-driven clinical decision-making, individualized therapeutic interventions, and predictive diagnostics. However, despite remarkable advances in machine learning (ML) and deep learning (DL), the widespread adoption of AI in healthcare remains constrained by the “black-box” nature of many computational systems. Clinicians, regulatory agencies, and patients increasingly demand transparency, interpretability, and trustworthiness in AI-guided medical recommendations. Explainable Artificial …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 13–29 Read article
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Atmospheric Boundary Layer Processes: Impacts on Weather Patterns and Climate Change
Abstract: The atmospheric boundary layer (ABL) is a vital component of the Earth's climate system, acting as the interface between the terrestrial surface and the overlying atmosphere. This layer, typically extending from the surface to a height of a few hundred meters, is characterized by strong gradients in meteorological variables such as temperature, humidity, wind speed, and atmospheric pressure. Understanding the dynamics of the ABL is essential for comprehending weather phenomena, …
Published in International Journal of Atmosphere · Vol. 1, Issue 2, 2024 · pp. 22–25 Read article
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Role of Inflammatory Markers and Lipid Abnormalities in Glycemic Dysregulation Among Type 2 Diabetics
Abstract: Background: Diabetes mellitus (DM) is a chronic metabolic disorder characterized by systemic inflammation and associated with various complications in multiple organs. Type 2 diabetes mellitus (T2DM) specifically involves insulin resistance, hyperglycemia, and inflammatory responses. This study investigates the levels of various inflammatory markers and their correlation with glycaemic control in T2DM patients. Objective: To evaluate the levels of inflammatory markers (including NLR, PLR, SII, SIRI, CRP, IL-6, TNF-α, TGF-β, MCP-1, …
Published in Emerging Trends in Metabolites · Vol. 2, Issue 2, 2025 Read article
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Mathematical Modeling of Epidemics Using Stochastic Differential Equations: A Review
Abstract: The accurate modeling of infectious disease dynamics is crucial for predicting outbreaks and informing public health interventions. While deterministic models such as the SIR (Susceptible-Infected-Recovered) framework have traditionally been used to understand disease transmission, they often fail to account for the randomness inherent in real-world scenarios. Disease spread is influenced by numerous uncertain factors, including individual behavioral changes, environmental fluctuations, and imperfect data reporting. These uncertainties can significantly impact model …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 1–6 Read article