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1126 articles for “predict”
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Machine Learning-Driven Force Analysis for Tool Wear Prediction Systems
Abstract: A system designed to forecast tool wear by utilizing a force sensor to monitor the wear of the tool's flank and applying a Convolutional Neural Network (CNN) for forecasting purposes. The methodology is demonstrated through experiments in milling, utilizing dry machining with a ball endmill on a stainless-steel component. The flank wear of the tool is directly assessed using a digital microscope throughout the operation. The forecasts produced by the …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 3, 2024 · pp. 16–25 Read article
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Comparative Analysis of Heart Disease Prediction System
Abstract: In the present world, where heart illnesses are on the rise, it is crucial to forecast these diseases. Performing the task on heart disease is a bit difficult and it must be finished precisely and successfully. Heart disease identification relies heavily on Machine Learning (ML) and data mining approaches. The primary focus of the review paper is that patients are easily prone to cardiac diseases depending on medical traits. Using …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 1, 2023 · pp. 1–6 Read article
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Strength Prediction and Optimization of Portland Limestone Cement Blended with Metakaolin and Rice Husk Ash
Abstract: This study explores the effects of Rice Husk Ash (RHA) and Metakaolin (MK) on the compressive strength of Portland Limestone Cement (PLC) mortar, aiming to promote sustainable construction materials. RHA and MK, derived from agricultural and industrial byproducts, serve as supplementary cementitious materials (SCMs) that offer environmental benefits and improve cement properties. Using response surface methodology (RSM) and central composite design (CCD), the research optimized the ternary blend of PLC, …
Published in International Journal of Minerals · Vol. 2, Issue 1, 2025 · pp. 1–14 Read article
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Data-Driven Predictive Analytics and Decision- Making in FinTech Using MongoDB and High-Throughput Data Pipelines
Abstract: This paper examines the implementation of MongoDB and high-throughput data pipelines within the financial technology (FinTech) sector to drive data-informed predictive analytics and decision-making. The study focuses on the architectural components, scalability, and challenges of integrating NoSQL databases into real-time data ingestion and analytics pipelines. The transformative potential of these technologies in modern financial systems is highlighted through practical use cases such as fraud detection, credit scoring, and personalized financial …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 1–15 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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Integration of Biomarkers in III and IV CKD Patients for Evaluation of Their Predictive Value for CVD in CKD Patients
Abstract: Background: Chronic kidney disease (CKD) is presently characterized by the presence of proteinuria and/or a diagnosis of renal impairment. The worldwide significance of CKD is underscored by the fact that its prevalence and incidence have doubled over the past three decades. This paper provides an overview of the existing evidence regarding biomarkers in individuals with CVD or CKD, with a particular focus on the emerging biomarkers (i.e., eGFR, sALB, UACR, …
Published in Research and Reviews: A Journal of Medicine · Vol. 15, Issue 3, 2025 · pp. 1–12 Read article
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Predictive Factors of Long-Term Sobriety: A Post-Discharge Outcome Study in Mangalore, Goa, and Vasai (2019–2023)
Abstract: Relapse following discharge remains a major challenge in addiction recovery, even with structured treatment protocols in rehabilitation centers. This study examines post-discharge outcomes from Kripa Foundation’s rehabilitation centers in Mangalore, Goa, and Vasai over a five-year period (2019–2023). A total of 100 patients were categorized into four behavioural outcome groups: Clean (Sober), Relapsed, R.I.P. (Deceased), and Unknown. The study aimed to identify demographic and behavioural predictors of sustained sobriety post-discharge. …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 · pp. 29–44 Read article
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A study on IoT and AI for Predictive Modeling and Control of Infectious Disease Transmission
Abstract: Background: The global response to novel and recurring infectious diseases is frequently hindered by surveillance systems that are slow, siloed, and reactive. Traditional epidemiology relies on retrospective analysis of clinical reports, often missing the critical early phase of autocatalytic spread. The urgency of modern public health necessitates a shift toward real-time, predictive intelligence. Methods: This study investigates the development and deployment of a synergistic paradigm integrating the Internet of Things …
Published in International Journal of Pathogens · Vol. 2, Issue 2, 2025 Read article
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Diabetes Risk & Al Nutrition Assistant
Abstract: The rising prevalence of diabetes mellitus has emerged as a major global health challenge. Early identification of individuals at risk, combined with personalized lifestyle-based interventions, can significantly reduce future complications. This study presents an AI-driven Nutrition Assistant integrated with a Diabetes Risk Prediction model. The system uses a machine learning classification approach to estimate the likelihood of diabetes based on clinical and nutritional factors, including body mass index, glucose levels, …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 31–38 Read article
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Early Alzheimer’s Disease Prediction Using Vision Transformers and Attention-Guided MRI Analysis
Abstract: Alzheimer’s Disease (AD) continues to be a major global health concern, with early detection being crucial for effective intervention. While conventional machine learning and convolutional neural network (CNN) approaches have made notable progress in automated AD diagnosis using MRI data, they often struggle with capturing long-range dependencies and maintaining spatial contextual awareness. In this research, we propose a novel framework using Vision Transformers (ViTs) for early Alzheimer’s prediction from 3D …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 30–40 Read article
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The Early Brain Hemorrhage Prediction System Using Machine Learning
Abstract: Brain hemorrhage is a critical medical emergency that requires immediate attention, as delays in diagnosis can result in severe neurological damage or death. The condition involves bleeding within or around brain tissues, leading to increased intracranial pressure and disruption of normal brain function. Although imaging techniques such as CT scans and MRI provide accurate diagnosis, their availability is limited in emergency and rural settings. In recent years, machine learning has …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 Read article
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Identification and Characterization of Genetic Predictors of Sickle Cell Anemia in Bilaspur District, Chhattisgarh, India
Abstract: In the present decades, sickle cell anemia (SCA) is a challenging task for control of hereditary syndrome in Bilaspur district of Chhattisgarh state, India. The present study aims to identify and characterize genetic predictors of SCA from Bilaspur district (CG) in 2024. A total of 3000+ individuals were screened and categorized into carriers, positive (screening), and diseased cases. Fetal hemoglobin (HbF) level is determined by several genetic factors including genetic …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 4, Issue 2, 2026 · pp. 1–9 Read article
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Industrial Prognostics via Ensemble Machine Learning: An Uncertainty Aware Framework for RUL Estimation on NASA FD004 Telemetry
Abstract: Estimating the Remaining Useful Life (RUL) of industrial machinery in real-time is now vital for both operational safety and smart resource management. In the aviation industry, turbofan engines deal with constantly shifting flight conditions, making traditional, scheduled maintenance both expensive and prone to error. This paper addresses the flaws in common “point-prediction” AI models, which offer a single failure date without any margin for error, by introducing a new, uncertainty-aware …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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Early Pregnancy Levels of Fasting Glucose, HbA1c, and Adiponectin as Predictors of Gestational Diabetes Mellitus Among Pregnant Women in Tamil Nadu, India
Abstract: Background: Gestational diabetes mellitus (GDM) is rapidly becoming a major public health issue across India, and Tamil Nadu continues to report some of the country’s highest incidence figures. Identifying women at elevated risk during the first trimester allows health workers to intervene early and improve outcomes for both mothers and babies. This research, therefore, examines whether fasting plasma glucose, glycated haemoglobin, and adiponectin measured at that initial visit can reliably …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 2, 2026 · pp. 10–18 Read article
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Prediction of temperatures and residual stresses during FSW of AA2024 and AA7075 with copper using HYPERWELD software
Abstract: This paper investigates the temperature at different workpiece and tool pin sections. In this investigation, various materials are utilized, for example, AA7050, AA2024, and Copper, for other process parameters. Tool rotational speed, tool tilt angle, and welding speed are process parameters. Thermal distribution results are examined with the assistance of these process parameters. Altair’s Hyper Weld, a preeminent computer-aided engineering (CAE) application for the simulation of friction stir welding, has …
Published in Journal of Polymer & Composites · Vol. 11, Issue 12, 2023 · pp. 101–112 Read article
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Time Series Sales Forecasting Using ARIMA Model
Abstract: Sales forecasting is a critical application in various industries and presents one of the most challenging problems worldwide. One method of prediction involves identifying patterns in historical data, where the outcome is known in advance and can be validated using more recent data. If a pattern consistently leads to the same outcome, it can be considered a genuine relationship. This method is highly flexible and can be utilized with diverse …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 1, 2024 · pp. 17–27 Read article
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Multi-factor Fused Light path QoT Prediction for Optical Net-works: A Multiple Reservoir Analysis Strategy
Published in Trends in Opto-electro & Optical Communication Read article
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Analyzing And Predicting the Battery Health of Battery Energy in EV’s
Abstract: The most widely used energy storage components in products like electric cars, portable electronics, and energy storage systems are lithium batteries. On the other hand, if lithium batteries are not regularly checked, they may perform worse, have a shorter lifespan, or even explode or cause serious harm. Our proposal is to develop a state of health monitoring system for lithium batteries and an algorithm for estimating the state of charge …
Published in Journal of Nuclear Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 28–37 Read article
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Machine Learning Driven Mobile Price Prediction Using Feature Selection and Parameter Optimization
Abstract: Machine learning calculations are utilized in many fields like money, training, industry, medication, and online business. Machine learning calculations show execution contrasts relying upon the dataset and handling steps. Picking the right calculation, preprocessing and post-handling techniques have incredible significance in accomplishing great outcomes. The Random Forest classifier, K-nearest neighbor classifier, and support vector machine methods are evaluated to forecast mobile phone price categories. The “prediction” dataset which is taken …
Published in Current Trends in Information Technology · Vol. 14, Issue 3, 2024 · pp. 18–25 Read article
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Machine Learning-Driven Early Prediction and Prevention of Obesity and Overweight
Abstract: Obesity has become a global health concern, with its prevalence reaching alarming levels in recent years. By classifying obesity-level, healthcare professionals can assess an individual's risk and develop appropriate treatment and prevention strategies. Healthcare professionals can customize interventions and create personalized treatment plans based on individual needs. This paper delivers a system provides an overview of obesity, highlighting the importance of accurate and standardized categorization for effective management and treatment …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 · pp. 31–40 Read article