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40 articles for “Risk Prediction”
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Prediction of Perineal Trauma During Childbirth By Assessment of Striae Gravidarum Score
Abstract: Perineal trauma is a common complication during vaginal childbirth, often resulting in short- and long-term maternal morbidity. Early prediction of women at risk can aid in preventive strategies and improve maternal outcomes. Striae gravidarum, commonly known as stretch marks, are skin changes that occur during pregnancy due to hormonal, mechanical, and genetic factors. Recent studies have suggested that the presence and severity of striae gravidarum may be associated with the …
Published in International Journal of Obstetrics, Perinatal and Neonatal Nursing · Vol. 11, Issue 1, 2025 · pp. 11–23 Read article
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Predictors of Cardiovascular Disease Risk Among adolescents in Indian Context
Abstract: India harbors the world's largest population of adolescents, marking a period of substantial transformation encompassing various facets, including physical, mental, emotional, and social aspects in an adolescent's life. There is a paucity of data on theprevalence of underweight, overweight, and obesity in Kerala, especially about the magnitude of the problem amongadolescents. Nurses play a key role in primordial prevention and thus limited studies on socioeconomic status (SES) and anthropometrics among …
Published in International Journal of Cardiovascular Nursing · Vol. 9, Issue 2, 2023 · pp. 9–16 Read article
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Comparison of predictive ability of stroke-associated pneumonia risk scores in acute hemorrhagic stroke
Abstract: Objective: To determine the best scoring system among 5 scores (Pneumonia score, PANTHERIS, ISAN score, A2DS2, ACDD4) for prediction of pneumonia after acute haemorrhagic stroke in Stroke Centre. Subjects and Methods: We carried out retrospective study of 508 patients with acute haemorrhagic stroke admitted to Department of Neurology of Pyongyang medical university from January 1, 2018 to August 1, 2022. Demographic and clinical traits of patients were collected and analysed. …
Published in International Journal of Nursing Critical Care · Vol. 10, Issue 2, 2024 · pp. 12–19 Read article
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Improving Safety Outcomes in the Construction Industry: A Study of Effective Safety Management Techniques
Abstract: Abstract The construction industry is notorious for its high rates of workplace accidents and fatalities, necessitating a critical evaluation of safety management practices. This paper investigates effective safety management techniques within the construction sector, emphasizing the integration of traditional safety measures with emerging technologies to enhance safety outcomes. A mixed-methods approach is employed, combining quantitative data analysis from industry reports and qualitative insights gathered from case studies of five construction …
Published in International Journal of Architectural Design and Management · Vol. 10, Issue 2, 2024 · pp. 15–20 Read article
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Assessment of Usage of Modelling and Simulation Software in Water Resource Engineering Management
Abstract: The use of software tools for modelling and simulation in the water sector is becoming increasingly important for sustainable water resource engineering management. This study X-rays the use of software for modelling and simulation in the water sector. Geospatial Data Abstraction Library (GDAL), Sea Surface Temperature (SST), Soil Water Assessment Tool (SWAT), Land Surface Analysis Satellite Applications Facility (LSA-SAF), data assimilation (DA), GIS, HEC-HMS, EPANET and many other software can …
Published in International Journal of Water Resources Engineering · Vol. 9, Issue 1, 2023 · pp. 11–20 Read article
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Prediction Models on Causing Factors for Delirium in Intensive Care Unit Patients
Abstract: This study aims to screen high-risk group for delirium in the intensive care unit by building optimal prediction models over multidimensional analysis of the factors causing delirium in intensive care unit patients, with providing the theoretical foundation for the development of protocols for delirium prevention and management in such patients. The data were collected over the electronic medical records by 3781 patients who were admitted to the medical/ surgical intensive …
Published in International Journal of Neurological Nursing · Vol. 3, Issue 1, 2017 · pp. 13–24 Read article
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Fintech Innovations and Their Impact on Global Markets
Abstract: Financial technology (fintech) is revolutionizing the global financial sector by improving efficiency, inclusivity, and transparency. By integrating technology with financial services, fintech innovations, such as blockchain, artificial intelligence (AI), digital wallets, and peer-to-peer lending are challenging conventional systems. These advancements not only increase the accessibility of financial services for underserved communities but also provide unmatched convenience to consumers and businesses globally. Blockchain, one of the most significant innovations, has transformed …
Published in International Journal of Software Computing and Testing · Vol. 11, Issue 1, 2025 · pp. 1–5 Read article
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Health Monitoring System for Fault Identification on Centrifugal Pump Using ML
Abstract: Centrifugal pumps are crucial equipment widely used in various industries, and their reliable operation is essential for maintaining production and preventing costly downtimes. This paper proposes a comprehensive health monitoring system for centrifugal pumps that combines model-driven and data- driven approaches, leveraging artificial intelligence (AI) and machine learning (ML) techniques. The system incorporates demand prediction using artificial neural networks and fault diagnosis employing different ML classifiers, such as decision trees …
Published in International Journal of Mechanics and Design · Vol. 10, Issue 2, 2024 · pp. 1–12 Read article
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Towards a Geotechnical Input-Based Conceptual Cost Estimating Methodology for Highway Projects
Abstract: The trend in the literature reveals a wide range of innovative approaches which have been proposed to improve the accuracy of conceptual estimates. These techniques are usually based on differing analytical approaches. Although these techniques obtain estimates that closely approximate actual costs, the requisite time and resources to gather sufficient data or obtain relevant information during initial project stages may not be possible. The study proposes that for a road …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 8, Issue 2, 2022 · pp. 28–37 Read article
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Optimized Fault Current Prediction for DFIG-Based Wind Turbines Using Type-I Fuzzy Logic Controller
Abstract: The increasing integration of Doubly-Fed Induction Generator (DFIG)-based wind turbines into modern power grids requires robust fault detection and prediction mechanisms to ensure stable and reliable operation. However, accurately predicting fault currents in such systems is challenging due to the nonlinear dynamics involved. This study presents an optimized fault current prediction framework using a Type-I Fuzzy Logic Controller (FLC) to address these challenges. The proposed approach effectively models the uncertainties …
Published in International Journal of Analog Integrated Circuits · Vol. 10, Issue 2, 2024 · pp. 41–50 Read article
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Predicting Mortality in Burn Patients in A Tertiary CareSetting Using the Revised Baux Score
Abstract: Burns are a significant risk factor contributing to mortality and morbidity, especially in underdevelopednations. While innovations in burn patient management have considerably reduced mortality rates indeveloped countries, the fatality rates remain unacceptably high in underdeveloped regions where theseadvancements have not been widely adopted or implemented. Accurate prediction of outcomes forsevere burn patients at the time of presentation is crucial for guiding clinical decisions and improvingpatient management. In developed countries, several …
Published in International Journal of Chemical Separation Technology · Vol. 10, Issue 1, 2024 · pp. 27–32 Read article
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AI-Integrated Precision Agriculture System for Fertilizer Optimization, Multimodal Crop Yield Prediction
Abstract: Agriculture is rapidly transforming into a data-driven ecosystem supported by advances in artificial intelligence (AI), Internet of Things (IoT) sensor networks, and satellite remote sensing technologies. These innovations enable precision-driven decision-making aimed at improving productivity while minimizing environmental impact. This paper presents an AI-integrated precision agriculture system designed to optimize fertilizer usage and enhance crop yield prediction accuracy through a robust multimodal deep learning framework. The proposed approach integrates heterogeneous …
Published in International Journal of Plant Biotechnology · Vol. 12, Issue 1, 2026 · pp. 11–17 Read article
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A Hybrid Approach to Secure Cloud Storage: Machine Learning and Blockchain Integration
Abstract: With the rapid adoption of cloud computing across industries, securing cloud storage has become a paramount concern for organizations that rely on cloud-based systems to manage sensitive data. Traditional security approaches often struggle with the complex and evolving nature of cyber threats, leading to vulnerabilities that malicious actors can exploit. In response to these challenges, this paper proposes a hybrid approach that integrates machine learning and blockchain technologies to create …
Published in International Journal of Distributed Computing and Technology · Vol. 10, Issue 2, 2024 · pp. 35–47 Read article
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Integrating Cellular Automata for Predicting Urban Expansion: A Case Study of Bavdhan, Sus, and Mahalunge
Abstract: Rapid Urban Expansion in the metropolitan cities like Pune, result in indiscriminate land use changes transforming natural landscapes. Such haphazard spatial development poses a risk to depletions of resources along with the disarray of the ecological system. A proactive approach to predicting and analyzing such changes is necessary in promoting the well-managed growth of cities. For the complex nature of urban growth, simulation method is used for analyzing spatial patterns, …
Published in International Journal of Town Planning and Management · Vol. 12, Issue 1, 2026 · pp. 51–62 Read article
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Smart Agro-Advisory Systems: AI-Based Platforms for Real-Time Farmer Decision Support
Abstract: Agriculture is a vital sector for food security and economic growth, particularly in the developing world. Farmers, however, often face unpredictability of weather conditions, insect attacks, wasteful use of resources, and uncertainties of the market. Farmers' practices are mostly based on experience and intuition, which might not always be the best to apply. Smart Agro-Advisory Systems (SAAS) based on Artificial Intelligence (AI) offer real-time decision support to farmers, enabling them …
Published in International Journal of Microwave Engineering and Technology · Vol. 11, Issue 1, 2025 · pp. 8–14 Read article
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Predictive Models for Drinking Water Quality: Leveraging Machine Learning for Improved Safety and Efficiency
Abstract: Quality of drinking water is one of the critical determinants of public health, leading to severe environmental and health-related issues when poor. The paper examines the integration of machine learning techniques that could improve accuracy and efficiency in assessing drinking water quality. The traditional techniques of monitoring drinking water are resource-intensive yet lack timely insight into contamination events. In this scenario, an evaluation of the performance of ML models such …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 11, Issue 1, 2025 Read article
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Machine Learning Approaches for Customer Churn Prediction in Telecommunications
Abstract: Customer churn prediction is a critical challenge for companies in the telecommunications industry. The competition is intense, and acquiring new customers can be costly. Predicting when existing customers might leave (churn) helps companies take proactive measures to retain them, reducing churn rates and costs. By analyzing historical customer data, including demographics, service usage, billing, and customer service interactions, this study aims to identify customers at risk of leaving their current …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 10, Issue 2, 2024 · pp. 1–7 Read article
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Predictive Analytics in E-Learning: Enhancing Student Performance Through Machine Learning Models
Abstract: With the explosion of electronic devices and internet technologies in today’s world, the amount of data we store has grown massively. Data is simply information that has been organized in a way that makes it easy to share or work with. A potent technology that enables computers to learn from data without direct programming is machine learning, which we employ in our research. The focus of this study is on …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 10, Issue 2, 2024 · pp. 1–5 Read article
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Review of Anomaly Detection Techniques in MANETs: AMachine Learning Approach to Intrusion Detection, Attack Prediction, and Routing Security
Abstract: Mobile Ad hoc Networks (MANETs) are decentralized, self-organizing networks that offer flexibility and scalability for a variety of applications. However, their dynamic topology and limited resources make them highly susceptible to security threats. Traditional security measures often struggle to address the complexities of evolving and sophisticated attacks within such networks. This paper reviews the role of machine learning (ML) techniques in enhancing anomaly detection capabilities in MANETs, focusing on their …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 2, 2026 · pp. 1–5 Read article
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Optimization of Effects of FMEA to Enhance Quality and Efficiency of CNC Machines in Valve Manufacturing Industry
Abstract: Failure mode and effects analysis (FMEA) is a systematic method for identification and preventing problems of products and process before its occurrence. FMEA focus on preventing defects, enhancing safety and increasing customer satisfaction. The FMEA needs to define parameters such as Severity (S), Occurrence (O), Detection (D) and Risk Priority Number (RPN). The conventional FMEA and grey relational analysis approaches are applied in this work. The rankings of the failure …
Published in International Journal of Computer Aided Manufacturing · Vol. 3, Issue 2, 2017 · pp. 11–20 Read article