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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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Clinical and Etiological Profile of Heart Failure Patients
Abstract: This study was undertaken to study the clinical and etiological profile of patients with heart failure at Mamata General Hospital, Khammam. This is a study of clinical and etiological profile of heart failure in patients of above 15 years of age, who were admitted in Mamata Medical College during the period December 2012 to November 2013. The incidence of heart failure (HF) in Mamata General Hospital is less compared to …
Published in Research and Reviews: A Journal of Medicine · Vol. 4, Issue 1, 2014 · pp. 6–11 Read article
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A Comparative Study of Timed Up and Go Test and Tinetti Performance Oriented Mobility Assessment in Predicting Falls in Hemiparetic Stroke Patients
Abstract: Hemiparesis following stroke is the most frequent cause of adult disability. Falls in stroke survivors are a consequence of stroke related locomotor deficits or balance deficits or gait disturbances. Falls are common following stroke but knowledge about predicting future fallers is lacking. The purpose of this study was to compare Timed Up and Go test (TUG) scores and Performance Oriented Mobility Assessment (POMA) scores for predicting falls in Hemiparetic patients …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 4, Issue 3, 2014 · pp. 14–18 Read article
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Toxicology 4.0: Integrating Artificial Intelligence, Big Data, Health Informatics, and Precision Analytics for Predictive Toxicity Assessment, Real-Time Toxicovigilance, and Personalized Patient Safety
Abstract: Background: Toxicology is undergoing a major transformation, increasingly described as Toxicology 4.0, driven by the integration of artificial intelligence (AI), big data analytics, health informatics, and precision analytics. Conventional toxicity testing is limited by high costs, lengthy timelines, and challenges in translating animal and low-throughput in vitro findings to humans. Aim and Objectives: To comprehensively evaluate the emerging role of Toxicology 4.0 in predictive toxicity assessment, real-time toxicovigilance, and personalized …
Published in Research and Reviews: A Journal of Toxicology · Vol. 16, Issue 2, 2026 Read article
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VolleyNexis AI: A Multimodal Artificial Intelligence Framework for Opponent Strategy Prediction, Tactical Intelligence, and Athlete Performance Optimization in Volleyball
Abstract: The rapid advancement of Artificial Intelligence (AI) has profoundly transformed sports analytics, enabling deeper insights, real-time data analysis, and enhanced performance predictions. Noticeable results have been seen by enabling automated analysis of complex gameplay patterns along with athlete performance. Volleyball is a dynamic and strategic sport, which requires continuous tactical adjustments and constant monitoring of the player’s performance. This paper presents VolleyNexis AI, which is a multimodal artificial intelligence framework …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 2, 2025 Read article
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AI-Optimized Nano-Silica Reinforced PCM Composites for Predictive Solar-Thermal Energy Storage Networks
Abstract: This study presents an AI-optimized nano-silica reinforced polymer composite phase change material (PCM) for predictive solar-thermal energy storage networks. The proposed composite combines paraffin wax, high-density polyethylene (HDPE), and uniformly dispersed nano-silica particles to improve thermal conductivity, structural stability, leakage resistance, and long-term cycling performance. The composite was fabricated through melt blending and ultrasonication-assisted nanoparticle dispersion, followed by comprehensive morphological, chemical, thermal, and thermophysical characterization using scanning electron microscopy (SEM), …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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Selected Heavy Metals Levels (Cu, Cr, Cd, Pb, Fe) in Gwadabawa Lake, Sokoto State, Nigeria
Abstract: The main aim of this work was to determine the concentrations of some heavy metals, specifically Cu, Cd, Pb, Cr and Fe in Gwadabawa lake, Gwadabawa Local Government, Sokoto State using standard methods (atomic absorption spectroscopy) and materials of analytical grade. The results were analyzed. The range of Fe concentration was 0.01 ± 0.001 to 1.37 ± 0.3(ppm), and range of Cu concentration determined was 0.00 to 0.02±0.008(ppm). The range …
Published in International Journal of Minerals · Vol. 1, Issue 1, 2024 · pp. 8–15 Read article
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Genomic Selection for Grain Yield in Wheat Using Machine Learning on DArT Molecular Markers: A Comparative Evaluation Across Multi-Environment Trials
Abstract: Genomic selection (GS) predicts complex quantitative traits directly from genome-wide molecular markers, bypassing the need for extensive phenotypic trials and accelerating plant breeding cycles. We conducted a comparative evaluation of seven regression approaches — ridge regression (the machine-learning equivalent of RR-BLUP), Lasso, Elastic Net, Partial Least Squares, linear Support Vector Regression, Random Forest, and Gradient Boosting — for predicting grain yield from 1,279 Diversity Array Technology (DArT) molecular markers genotyped …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article
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Kinetics of Ion-Isotopic Exchange Reactions using Nuclear Grade Resins Purolite NRW-4000 and Purolite NRW-60
Abstract: AbstractThe paper deals with an application of nondestructive radio isotopic tracer technique in performance evaluation of two nuclear grade anion exchange resins Purolite NRW-4000 and Purolite NRW-6000. The technique was used to study the kinetics of bromide and iodide ion-isotopic exchange reactions taking place between the external ionic solution and the resin surface for which 131I and 82Br were used as tracer isotopes. It was observe that at a constant …
Published in Journal of Nuclear Engineering & Technology · Vol. 4, Issue 1, 2014 Read article
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Knowledge on Atypical Antipsychotic Drugs among Caregivers of Mentally Ill Patients
Abstract: Antipsychotic drugs have high rate of nonadherence due to unpleasant side effects. This study aimed to assess the caregivers’ knowledge on atypical antipsychotic drugs. A descriptive survey approach was used. The study was conducted among 100 caregivers of mentally ill patients receiving atypical antipsychotic drugs. The data were collected through a self-administered knowledge questionnaire on atypical antipsychotic drugs. The data were analyzed by using descriptive and inferential statistics. Results showed …
Published in Journal of Nursing Science & Practice · Vol. 5, Issue 3, 2015 · pp. 36–40 Read article
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Clinical Significance of Immune Cells and T-cell Subsets in Lung Cancer
Abstract: Objectives: The aim of the study was to determine the clinical usefulness of pretreatment hematological parameters including neutrophils, lymphocytes, monocytes and immune T-cell subsets as well as calculated coefficients such as neutrophils-to-lymphocytes ratio(NLR),monocytes-to-lymphocytes ratio(MLR) and platelets-to-lymphocyte ratio(PLR)in patients with lung cancer. Materials and Methods: A total of 102 patients with lung cancer were prospectively analyzed. T-cell subsets were assessed by flow cytometry method. Peripheral blood was collected from 25 healthy …
Published in Research and Reviews : A Journal of Immunology · Vol. 9, Issue 2, 2019 · pp. 14–29 Read article
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Comparison between two severity classificaitons in patients with acute cholecystitis
Abstract: Background and objective: Assessment severity helps clinicians to guide appropriate treatment and minimumize adverse outcome. The objective of our study was to comparison between TG13 severity system and EGS grade system for predicting clinical outcomes in acute cholecystitis. Patients and method: This is a retrospective single-center study which enrolled patients who were admitted to pyongsong medical university hospital between February 2020 and October 2021. Tokyo 2013(TG 13) severity classification and …
Published in Research and Reviews : Journal of Surgery · Vol. 12, Issue 2, 2023 Read article
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Model to Predict a Ratio Control of Hydrocarbon Acid and Water in a Packed Bed Reactor
Abstract: Model development was carried out to examine the ratio of hydrochloric acid gas and water in a packed bed reactor. The research predicted increase in output with increase in time, revealing the effectiveness ratio control of hydrochloric acid separation from water using absorption column mechanism. The density of the products played an active role in the separation process as well as in control action function. The developed model can be …
Published in Emerging Trends in Chemical Engineering Read article
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Experimental Study on Heart Disease Prediction Using Different Machine Learning Algorithms
Abstract: Heart disease which can also be referred to as the cardiovascular disease is one of the raising concerns in today’s world. It is one of the major health problems causing death among humans irrespective of the age group and therefore has made it necessary to look into different medical factors that are required to predict the same in advance using the collected historical datasets of various patients. Thus we have …
Published in Journal of Artificial Intelligence Research & Advances Read article
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A Novel Hybrid Link Prediction Algorithm for E-Commerce Recommender System Based upon Common Neighbor and Resource Allocation Methods
Abstract: Link prediction is a challenging task in recommender systems, as it requires the ability to accurately predict future links between users and items. In this study, we propose a novel hybrid link prediction algorithm for e-commerce recommender systems that combines the common neighbor and resource allocation methods. The common neighbor method is a straightforward and intuitive algorithm that calculates the number of shared neighbors between two nodes. The intuition is …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 1, 2023 · pp. 12–17 Read article
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Machine Learning Based Early Cataract Detection: A Predictive Modeling Approach
Abstract: Cataracts, characterized by dense cloudy areas in the eye’s lens, afflict more than 50% of elderly individuals, leading to impaired vision and potential blindness. Detecting cataracts at an early stage is crucial to facilitate simpler treatments, as neglecting the condition may necessitate complex eye surgery. To address this issue, we are creating a predictive system that identifies cataract disease by analyzing user-provided eye features. To achieve this, we leverage OpenCV, …
Published in International Journal of Computer Science Languages · Vol. 1, Issue 2, 2023 · pp. 1–8 Read article
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Service Life Prediction of Concretes Incorporated with Ground Granulated Blast Furnace Slag and Icrete with respect to Chloride Ion Penetration
Abstract: The reduced service life of concrete structures in coastal or de-icing salt conditions is commonly attributed to corrosion generated by chloride. Therefore, extensive research is being conducted to estimate the time taken for threshold chloride ions to reach the reinforcement and break the protective layer, initiating the corrosive process. This study conducted an experimental investigation on controlled concrete, concrete incorporating 50% GGBS, and concrete incorporating both 50% GGBS and 2% …
Published in Journal of Polymer & Composites · Vol. 12, Issue 1, 2024 · pp. 214–226 Read article
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Nanotechnology-Enhanced Wearable Biosensors for Liver Disease Detection: Integration with AI for Predictive Analytics
Abstract: The worldwide health burden of liver diseases is substantial, and effective treatment and management depend heavily on early detection. This study investigates the integration of nanotechnology-enhanced wearable biosensors with artificial intelligence (AI) techniques for predictive analytics in liver disease detection. The construction of extremely selective and sensitive biosensors that can identify a variety of biomarkers linked to liver illnesses has been made possible via nanotechnology. These nanotechnology-based biosensors can be …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 14, Issue 1, 2024 · pp. 22–36 Read article
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Data Handling Algorithms for the Healthcare System for the Prediction of Diabetes in Health Data Science (HDS): A Review Report
Abstract: In recent years, diabetes has become the biggest disease in different countries around the world. This disease is caused by adulteration in food ingredients, unhealthy food habits, a lack of physical exercise, and changing the lifestyle every time without a routine chart. The main objective of this review paper is to provide a proper understanding of the machine learning algorithm used in the healthcare system to handle diabetic patients' data. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 1–10 Read article
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Unlocking The Bioactivity Potential: Molecular Insights and Predictions of Salen, Salophen, Allicin, Curcumin, and Piperine
Abstract: In this work, the prediction of the biological activity of several significant molecules, including salen, salophen, allicin, curcumin, and piperine, are discussed. Using Molinspiration software, the molecular properties of these compounds were calculated. These molecules are highly significant due to their extensive potential in medical applications. Salen and salophen, for instance, play crucial roles in cancer chemotherapy and act as inhibitors of angiogenesis. Curcumin is renowned for its antioxidant properties, …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 14–21 Read article
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Association Rule Mining for Predicting Heart Disease: Challenges and Opportunities
Abstract: The exponential growth of digital healthcare data has spurred innovative applications of data mining techniques in medical research and practice. Among these, association rule mining stands out for its ability to uncover meaningful correlations within diverse datasets, such as electronic health records, imaging data, and genetic information. This paper reviews the application of association rule mining in predicting heart diseases, emphasizing its potential to enhance early detection, risk stratification, and …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 3, 2024 · pp. 29–34 Read article