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1983 articles for “failure-prediction AUROC of 0.967” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Predictive Modeling System for Automated Skin Lesion Classification Using Deep Neural Networks and Voting Ensembles
Abstract: Skin cancer is one of the most prevalent cancers globally. Early and accurate diagnosis is critical for timely treatment and improved prognosis. This study presents a predictive modeling system for automated classification of skin lesions from dermoscopic images using deep neural networks and voting ensemble techniques. A customized 16-layer convolutional neural network architecture is developed for feature learning from lesion images. The concept of horizontal voting ensemble is implemented by …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 29–35 Read article
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In silico Prediction of Two New Conformations of Aβ42 Peptide and Possible Mechanism of Their Aggregation
Abstract: Alzheimer’s disease is one of the most studied neurodegenerative diseases. The cause for most cases of this disease is unknown. However, there are many hypotheses regarding the progression of this disease. One of the hypotheses is the amyloid hypothesis. Amyloid precursor protein present on chromosome 21 is cleaved by β and γ sectretases. The cleaved fragments of this protein, nearly 36–43 residues long aggregates and are deposited as plaque in …
Published in Research and Reviews : Journal of Computational Biology · Vol. 8, Issue 1, 2019 · pp. 1–7 Read article
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Determination of The Mean Fetal Biometrics and The Mean of Ratio of biometrics in 2nd and 3rd Trimester of Pregnancy in Correlation with Fetal Gestational Age: As a Predictive Biometric Parameters
Abstract: Introduction: Fetal cerebellar diameter in normal gestation is also highly correlated with fetal growth indices. Objective: To determine to mean fetal biometric ratios in 2nd and 3rd trimester of pregnancy on ultrasound as a predictive biometric parameter of gestational age. Study Design: Cross-sectional study. Material and Methods: A total of 140 pregnant women in their second and third trimester were included in this study. BPD, AC, FL and TCD were …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 7, Issue 3, 2018 · pp. 12–16 Read article
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Prevalence and Predictors of Goiter among 6–12 years Old Children in Eastern Tigray Region, Northern Ethiopia: A Community-based Cross-sectional Study
Abstract: Iodine deficiency disorder (IDD) is the collective name of endemic goiter and endemic cretinism. Goiter is the main preventable major public health problem worldwide during pregnancy and childhood in an environment where iodine is deficient. The aim of this study was to assess the prevalence rate and associated factors of goiter among 6–12 years old children in eastern Tigray region, Northern Ethiopia. We used community-based cross-sectional survey. The study population …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 6, Issue 2, 2017 · pp. 52–60 Read article
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Digital Twin Assisted Intelligent Prediction of Polymer Composite Degradation Under Environmental Exposure
Abstract: Polymer matrix composites (PMCs) deployed in aerospace, marine, automotive, and renewable-energy structures are continuously subjected to coupled environmental stressors — ultraviolet (UV) radiation, moisture ingress, thermal cycling, and mechanical loading — that progressively degrade their mechanical performance. Conventional accelerated ageing tests and empirical lifetime models are time-consuming, destructive, and poorly suited to in-service, asset-specific degradation forecasting. This paper proposes a Digital Twin (DT) assisted intelligent prediction framework that fuses a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Graph Neural Networks for Molecular Scale Property Prediction and Inverse Design of Thermoset Polymer Nanocomposites: A Computational Framework
Abstract: Thermoset polymer nanocomposites exhibit properties that are highly sensitive to molecular scale formulation decisions, yet the vast design space remains largely unexplored because of the high cost of experimental characterisation and fully atomistic simulation. This paper presents TNC GNN, a dual mode graph neural network framework developed for the computational design of thermoset nanocomposite formulations. The forward module employs an attention augmented Message Passing Neural Network with 3D geometric encoding …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Implement Artificial Intelligence and Machine Learning for Engineering Design, Predictive Modeling, and Optimizing Polymer Nanocomposites
Abstract: Polymer nanocomposites are high performance engineered materials obtained by inclusion of nano-sized fillers into the polymer matrix to enhance mechanical, thermal, electrical, barrier and functional properties. However, the complex and non-linear interactions among polymer chemistry, nanofiller characteristics, filler concentration, dispersion, interfacial bonding and processing conditions make it challenging to anticipate and maximize their properties. Artificial intelligence (AI) and machine learning (ML) offer powerful data-driven solutions to these difficulties by establishing …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Optimization of Maximum Charge Per Delay Using Site-Specific Ground Vibration Prediction Models for Safe Blasting in an Opencast Coal Mine
Abstract: Drilling and blasting are critical operations in opencast coal mining that directly influence rock fragmentation, excavation efficiency, and production performance. However, excessive blast-induced ground vibration and air overpressure can create safety and environmental concerns, particularly in mines located near villages and sensitive structures. The present study was conducted at Chapapur-II Colliery, Mugma Area, Eastern Coalfields Limited (ECL), with the objective of optimizing blast design through the determination of safe maximum …
Published in Journal of Geotechnical Engineering · Vol. 13, Issue 2, 2026 · pp. 1–13 Read article
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Model to Predict a Split Range Control of Hot and Cold Water System
Abstract: Mathematical model was developed to monitor, predict, and stimulate hot and cold water system using split range control application. Computer program language of MATLAB software of ODE function was applied to monitor the trend of temperature parameter in the system. Result obtained revealed decrease in temperature value of the hot water and increase in the temperature value of cold water until equilibrium was attained at 132°F at > 1.0 h. …
Published in Journal of Water Pollution & Purification Research Read article
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Prediction of Molecular Targets for Anthraquinone and Its Analogs for Treatment of Good Pasteur Syndrome
Abstract: Objective: In order to find prospective molecular targets for the treatment of Good Pasteur Syndrome (GPS), a rare autoimmune disease that affects the kidneys and other organs, computational methods and network pharmacology were applied in this work. The goal of the study is to identify particular human proteins that might interact with anthraquinone and its analogues as well as to uncover potential mechanisms of action by which these drugs might …
Published in International Journal of Bioinformatics and Computational Biology Read article
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Conceptualization of An Intelligent Decision Framework for Control Factors and Weld Quality Prediction
Abstract: To improve the robot's welding quality, control welding precision, optimize welding parameters, realize continuous welding quality database optimization, and increase welding defect detection, a fuzzy neural network-based intelligent decision-making system must be built. This study demonstrates how fuzzy control theory and BP neural networks may be used to identify welding issues and enhance process variables. The experimental findings indicate that, with seam classification accuracy close to 90%, enhancing welding parameters …
Published in Journal of Polymer & Composites · Vol. 11, Issue 6, 2023 · pp. 10–19 Read article
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Tools, Modern Drugs, and Latest Investigations for the Diagnosis and Treatment of Heart Failure: A Systematic Review of the General Causes
Abstract: Heart failure (HF) diagnosis and treatment present formidable challenges, given the absence of a definitive single test. This systematic literature review aims to comprehensively analyze the current landscape of diagnostic tools, modern drugs, and latest investigative approaches in HF management. Recognizing the complexity of HF etiology, this systematic review emphasizes the importance of advanced diagnostic methods, such as genetic testing and artificial intelligence applications. The systematic review was conducted to …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 1, 2024 · pp. 1–10 Read article
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Social Capital as a Predicting Indicator to Measure the Psychological Health Impacts of COVID-19 Pandemic on Urban Societies in Pakistan.
Abstract: The COVID-19 pandemic has forced people to adapt to massive changes in their lifestyles; from health to work and how they interact with everyone nearby they know. This study aims to investigate the psychological wellbeing-impacts of COVID-19 on social capital in Pakistan. Social capital means the social and cultural coherence (as a predicting indicator) in the society. This was a survey based study conducted in 5 major cities (Islamabad, Rawalpindi, …
Published in International Journal of Urban Design and Development · Vol. 2, Issue 1, 2024 · pp. 12–21 Read article
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Analyzing Failures and Challenges in Oncology: Integration of Artificial Intelligence in Healthcare
Abstract: The present study focused on investigating the challenges and failures that had been embarked during the deployment of artificial intelligence technologies within the field of oncology in healthcare. Through precise research and statistical analysis, we aimed to elucidate the specific circumstances surrounding each failure, providing insights into the root causes, consequences, and subsequent developments. The present study was aimed to offer a detailed understanding of the challenges faced through artificial …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 1, 2024 · pp. 42–50 Read article
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Comparative Study to Assess the Knowledge of Higher Secondary School Students Regarding Career Counselling in Selected Rural and Urban Schools of Kashmir
Abstract: Background: Career counseling assists individuals in choosing appropriate educational and occupational choices and making career options based on future employment demands and requirements. Career counseling comprises a wide variety of professional activities that assist people in overcoming career-related obstacles. Aim: The primary objective of the study was to evaluate the understanding of career counseling among students in chosen rural and urban high schools in Kashmir. Method: This study employed a …
Published in Research and Reviews: A Journal of Health Professions · Vol. 14, Issue 1, 2024 · pp. 11–18 Read article
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A Review on Loan Approval Prediction Based on Machine Learning Techniques
Abstract: The banking industry has also benefited greatly from technological advancements. An increasing number of individuals are submitting loan applications on a daily basis. When deciding which loan applicants to approve, the bank must take certain rules into account. The bank needs to choose the best one for approval based on certain characteristics. The process of carefully verifying every person and recommending them for loan approval is laborious and fraught with …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 1–11 Read article
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Post Pandemic Cardiac Prediction: Analysing Heart Attack Mortality Rate In Vaccinated Adults
Abstract: Heart disease has emerged as a prominent contributor to global mortality rates. Discovered it early and providing timely management can significantly reduce the incidence of heart failures, death rates, and diagnostic costs associated with heart disease. In this study, we propose employing notification system to assess the risk of heart disease and explore potential associations between vaccination status and mortality rates due to heart attack among adult populations in the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 14, Issue 2, 2024 · pp. 45–51 Read article
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Prediction of Mobile Phone Price Using Machine Learning Classifiers
Abstract: One cannot imagine one's life without mobile phones; in today's digital era, mobile phones have become a necessity for everyone to fulfil their various demands like messaging, communication, entertainment, productivity, research, shopping and many more. In a thriving market of mobile phones where new smartphones are launched every year with new advanced features and various designs, determining the expense of a mobile can be a trouble-some tasks for consumers. In …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 101–108 Read article
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Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
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Automatic Stroke Recovery Rate Prediction System Based on Movement Analysis During Computer Interaction
Abstract: Stroke is a major health concern worldwide, often resulting in impaired motor functions and affecting the quality of life for affected individuals. This research introduces an innovative approach for predicting stroke recovery rates by leveraging movement analysis during computer interaction. The proposed system aims to provide a non-invasive and automated solution to assess the rehabilitation progress of stroke survivors. The system utilizes advanced motion tracking technologies to capture and analyze …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 76–82 Read article