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196 articles for “learning outcomes”
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Predictive Analytics and Adaptive Learning: A Machine Learning Framework for Reducing Learning Gaps
Abstract: Most contemporary digital learning environments encounter persistent challenges when it comes to accurately identifying students who are at-risk of academic underperformance. These challenges often arise due to limited visibility in learners’ engagement levels and gaps in conceptual understanding, particularly during the early stages of a course. To address this issue, the present study proposes an early prediction framework that leverages comprehensive student-related data through the application of machine learning techniques. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 16–21 Read article
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Assessment of The Impact of Online Learning Platforms on Academic Motivation
Abstract: Since the COVID-19 pandemic, online learning platforms have become an integral component of higher education systems worldwide. Digital platforms such as Google Classroom, Zoom, Moodle, and Microsoft Teams have transformed the way students access educational content and interact with instructors. While these platforms offer advantages such as flexibility, accessibility, and diverse multimedia resources, their influence on students’ academic motivation remains a critical concern. The present study aims to assess the …
Published in Recent Trends in Social Studies · Vol. 3, Issue 1, 2026 · pp. 13–18 Read article
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Harnessing AI and NLP to Transform Pharma Education Personalization, Learning, and Skill Development
Abstract: Particularly with NLP technologies, it is revolutionizing pharmaceutical education, enhancing human creativity, personalizing learning, and improving student outcomes. AI models like those from Open AI’s Chat GPT are increasingly integrated into educational practices that offer a solution to issues, such as teacher shortages, resource limitations, and the inefficient use of traditional teaching methods. This paper explores the diverse ways through which AI and NLP technologies are transforming pharma education within …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 1, 2025 · pp. 7–13 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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Semantics Analysis of Expected Goals in Soccer Data Using Machine Learning
Abstract: In recent years, the increasing availability of soccer data has greatly enhanced the accuracy and depth of player performance evaluation. Soccer, being one of the most popular sports worldwide, attracts millions of fans due to its simple rules, minimal equipment requirements, and high entertainment value. However, analyzing an entire match manually can be time-consuming, leading to a growing demand for automated methods that can summarize and interpret game data efficiently. …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 31–47 Read article
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AIducate: Your Smart Tutor–A Survey
Abstract: The ongoing “datafication” of our social reality has led directly to the emergence of new data-driven business models across various sectors, including education. As a result, the market for educational services is rapidly expanding. Educational technology (EdTech) companies are at the forefront, offering data-driven pedagogical solutions that are reshaping the landscape of learning. Despite the market's growth, few companies are harnessing the full potential of artificial intelligence (AI) and machine …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 2, 2024 · pp. 25–30 Read article
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Revolutionizing Education: Harnessing The Power of AI for Unparalleled Student Learning Advancements
Abstract: In recent years, advances in AI technologies have opened new possibilities for revolutionizing the education landscape. This research work delves into the potential of AI to revolutionize education and propel student learning to unprecedented heights. The study explores the application of AI in various educational contexts and its impact on personalized learning, instructional methodologies, and overall educational outcomes. The materials used in the research encompass academic articles, case studies, and …
Published in Current Trends in Information Technology · Vol. 14, Issue 1, 2024 · pp. 18–25 Read article
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A Comparative Study of different Techniques to predict Maternal Morbidity and Mortality Model
Abstract: Artificial intelligence (AI) encompasses a range of techniques, including machine learning and deep learning, which are increasingly utilized in the healthcare sector for tasks such as disease diagnosis and drug discovery. To achieve accurate disease diagnosis through AI, it is essential to integrate data from multiple medical sources, including ultrasound imaging, magnetic resonance imaging (MRI), mammography, genomics, and computed tomography (CT) scans, among others. This article presents a comprehensive review …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 1, 2025 Read article
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AI-Enhanced Interpretation of Cardiac Troponins: Toward Predictive Precision in Myocardial Injury
Abstract: Background: Cardiac troponins (cTn) represent the gold standard biomarkers for myocardial injury detection, yet their interpretation remains challenging due to various confounding factors and clinical contexts. Artificial intelligence (AI) technologies provide remarkable possibilities to improve the interpretation of troponin levels by utilizing pattern recognition, predictive modeling, and clinical decision-making support. Objective: This review examines the current state and future potential of AI-enhanced cardiac troponin interpretation, focusing on machine learning applications, …
Published in Research and Reviews: A Journal of Medicine · Vol. 15, Issue 3, 2025 · pp. 1–9 Read article
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Breast Cancer Detection Using Machine Learning: A Comparative Analysis of Supervised Learning Algorithms
Abstract: Globally, breast cancer remains a predominant cause of mortality among women, highlighting the urgent need for timely and precise diagnostic approaches. This research explores the application of machine learning algorithms—including Logistic Regression, SVM, Naïve Bayes, KNN, and Random Forest—on the Wisconsin Breast Cancer Dataset for effective tumor classification. Key pre-processing steps such as missing value handling, feature scaling, and dimensionality reduction were employed to improve model performance. The study evaluated …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 46–52 Read article
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Diabetes Prediction Using ML Techniques
Abstract: Diabetes mellitus, commonly referred to as diabetes, denotes a cluster of prevalent endocrine disorders characterized by persistent elevated levels of blood sugar. Diabetes is classified into two main types: type 1 and type 2. Type 1 diabetes arises when the body is unable to produce insulin, while type 2 diabetes involves either insulin resistance or insufficient insulin production. Early detection and intervention are essential to reduce its harmful impacts. The …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
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Advances in Simulation and Surgical Skill Training Evolution: Narrative Integrative Review
Abstract: Simulation-based education has emerged as a cornerstone of contemporary general surgery training, driven by increasing emphasis on patient safety, competency-based education, and rapid technological innovation. Traditional apprenticeship models, while foundational, are constrained by reduced operative exposure, work-hour limitations, and variability in clinical case mix. In this context, simulation provides a structured, reproducible, and safe environment for acquisition, assessment, and refinement of surgical skills across the training continuum. This narrative review …
Published in Research and Reviews : Journal of Surgery · Vol. 15, Issue 1, 2026 · pp. 7–13 Read article
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AI Approaches in Gait and Posture Analysis: A Review
Abstract: This review synthesizes current research on the application of artificial intelligence (AI) in gait and posture analysis, focusing on methodologies, algorithms, and clinical applications. It examines the use of machine learning (ML) and deep learning (DL) techniques to extract relevant features from sensorderived data, offering objective, and automated assessments that surpass traditional methods. A systematic literature review was conducted, analyzing studies that utilized AI for gait and posture analysis with …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 1–3 Read article
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Exploring the Potential of AI-Driven Personalized Learning and Cognitive Interventions for ADHD Management in Indian Children and Adolescents: A Focus on Early Intervention
Abstract: Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental condition that significantly impairs attention, executive functioning, and behavioural regulation in children and adolescents. In India, the management of ADHD is particularly challenging due to low public awareness, social stigma, and a critical shortage of specialized mental health services, especially in rural areas. These systemic barriers often lead to delayed diagnoses and limited access to consistent care. However, with the rapid …
Published in International Journal of Brain Sciences · Vol. 2, Issue 2, 2025 · pp. 1–5 Read article
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A Comprehensive Review on Federated Learning in Disease Detection
Abstract: Healthcare data, which is frequently dispersed among various organisations, has enormous potential to improve predictive analytics and illness identification. However, there are substantial privacy & legal obstacles to sharing this private data for centralised model training. Federated Learning is a paradigm shift that allows several organisations to work together to build a global model without disclosing raw patient information. Federated Learning uses a larger dataset to provide more reliable insights …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 1–21 Read article
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Diabetes Risk Prediction from Survey Data Using Machine Learning Algorithms
Abstract: Diabetes mellitus represents one of the most significant global health challenges, affecting millions worldwide and leading to severe complications if left undiagnosed or poorly managed. Early detection and risk assessment are crucial for preventing the progression of this chronic condition. This research presents a comprehensive machine learning approach for predicting diabetes risk using survey-based health parameters. The study implements and compares four prominent classification algorithms: Logistic Regression, K-Nearest Neighbors (KNN), …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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A Study on the Role of Artificial Intelligence in Indian Higher Education System
Abstract: In the present era, Artificial Intelligence (AI) has been transforming learning, teaching, and engaging, by making them more personalized and efficient in every field. In Indian Higher Education system, the application of Artificial Intelligence (AI) technology is improving learning techniques, by natural language processing, machine leaning etc. by students for analyzing data, using algorithms, discovering patterns and making the predictions for outcomes; and instructors may make lessons for each student …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 08–12 Read article
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Revolutionizing Wireless Communication: AI & ; ML in the Era of 6G
Abstract: With rapid technological advancement, sophisticated techniques are significantly enhancing the performance of wireless networks. In parallel, the growth of artificial intelligence (AI) has empowered systems to perform intelligent decision-making, automate processes, analyze data, generate insights, and predict future outcomes. AI systems are now capable of learning and adapting to dynamic environments. Particularly, machine learning and deep learning techniques have achieved remarkable success across a wide range of applications in recent …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 3, 2025 · pp. 29–36 Read article
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A Study to Evaluate the Effectiveness of Planned Teaching Program on Diabetic Management Regarding Knowledge and Practice Among Patients with Diabetes Mellitus at Selected Taluk Government Hospital, Kollegala
Abstract: Diabetes mellitus is a chronic metabolic disorder with a growing global impact. Effective management of this condition requires not only medical intervention but also comprehensive patient education. This study was conducted to evaluate the effectiveness of different diabetes education methods on improving metabolic control, body mass index (BMI), and blood pressure among diabetic patients. The research aimed to empower individuals with diabetes by enhancing their knowledge and self-management skills. A …
Published in Journal of Nursing Science & Practice · Vol. 15, Issue 3, 2025 · pp. 19–28 Read article
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Deep Learning -Based Dental Issue Detection
Abstract: Dentistry is vital for preserving oral health, a key component of overall wellness. Early identification of dental issues is crucial for effective treatment and avoiding further complications. Conventional approaches to diagnosing dental problems typically depend on physical examinations and visual assessments by skilled professionals, which can be both time-intensive and influenced by individual judgment.In recent years, the application of deep learning algorithms has demonstrated significant potential in automating and enhancing …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 1, 2025 · pp. 18–23 Read article