Relevant bibliographies by topics / Predicting life expectancy

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Predicting life expectancy'

Author: Grafiati
Published: 4 June 2021
Last updated: 28 July 2025

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Journal articles on the topic "Predicting life expectancy"

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Das, Antora, Md Mahfuz Uddin, and Md Rezaul Karim. "Predicting Life Expectancy using Machine Learning Techniques." International Journal of Statistical Sciences 25, no. 1 (2025): 55–70. https://doi.org/10.3329/ijss.v25i1.81045.

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Life expectancy is a key measure of a country's overall health, socioeconomic development, and quality of life. The main objective of the study is to identify key factors influencing life expectancy using ‘Cleaned-Life-Exp’ standardized data from the World Health Organization (WHO) and to compare the performances of life expectancy prediction using various machine learning algorithms. The key influencing features on life expectancy are selected using Boruta and Regularized Random Forest (RRF) algorithms. Eight machine learning models such as Linear Regression (LR), Decision Tree (DT), Random F
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Terret, C., and J. P. Droz. "11 Prostate cancer: predicting life expectancy." Critical Reviews in Oncology/Hematology 78 (May 2011): S8. http://dx.doi.org/10.1016/s1040-8428(11)70030-0.

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Yancy, Clyde W. "Predicting Life Expectancy in Heart Failure." JAMA 299, no. 21 (2008): 2566. http://dx.doi.org/10.1001/jama.299.21.2566.

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TEJA, KALLAKURI SAI, and R. BHANU SANKAR. "Predicting Life Expectancy Using Machine Learning Techniques on Who Data." International Scientific Journal of Engineering and Management 04, no. 07 (2025): 1–9. https://doi.org/10.55041/isjem04842.

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This project applies machine learning algorithms to predict life expectancy using WHO datasets. It aims to discover relationships between socio-economic indicators, health expenditure, and life expectancy. Data preprocessing involved handling missing values, encoding categories, and scaling features. Regression models like Linear, Polynomial, Decision Tree, and Random Forest were used for GDP-expenditure analysis. Model performance was evaluated using R² score, RMSE, and visualized through prediction plots. Logistic Regression was applied to classify countries as 'Developed' or 'Developing' ba
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Palmer, Duncan, and Niel Krige. "Real age-adjusted life expectancy." Journal of Economic and Financial Sciences 6, no. 1 (2013): 153–66. http://dx.doi.org/10.4102/jef.v6i1.281.

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This study summarises the development of a model to determine an individual’s adjusted life expectancy based on his Real Age. The model incorporates aspects such as gender, residing province, income, HIV status, ethnic background, weight, exercise, family illness history, stress, substance abuse and diet. Predicting life expectancy is vital in retirement planning for two reasons: 1) given the diverse nature of South Africa, the national average life expectancy cannot be applied to everyone; and 2) retirement duration forms a vital part in the retirement planning process. Retirees can make more
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Clayton, Douglass B., and Donald A. Urban. "Point: TheValue of Predicting Life Expectancy in Men with Clinically Localized Prostate Cancer." Journal of the National Comprehensive Cancer Network 5, no. 7 (2007): 703–8. http://dx.doi.org/10.6004/jnccn.2007.0062.

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The prediction of life expectancy in prostate cancer screening and treatment is a controversial topic that evokes various opinions regarding its validity. The authors believe incorporating life expectancy prediction into the treatment algorithms for prostate cancer is important. Using a combination of clinical judgment and specific predictive tools, physicians can estimate the life expectancy of patients with prostate cancer. These estimates can then be used to help guide treatment discussion. Estimating life expectancy benefits older men in whom decisions regarding the best form of treatment
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Jeldres, Claudio, Jean-Baptiste Latouff, and Fred Saad. "Predicting life expectancy in prostate cancer patients." Current Opinion in Supportive and Palliative Care 3, no. 3 (2009): 166–69. http://dx.doi.org/10.1097/spc.0b013e32832e9c80.

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Kouame Amos, B., and I. V. Smirnov. "Determinants in Predicting Life Expectancy Using Machine Learning." Advanced Engineering Research 22, no. 4 (2023): 373–83. http://dx.doi.org/10.23947/2687-1653-2022-22-4-373-383.

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Introduction. Life expectancy is, by definition, the average number of years a person can expect to live from birth to death. It is therefore the best indicator for assessing the health of human beings, but also a comprehensive index for assessing the level of economic development, education and health systems . From our extensive research, we have found that most existing studies contain qualitative analyses of one or a few factors. There is a lack of quantitative analyses of multiple factors, which leads to a situation where the predominant factor influencing life expectancy cannot be identi
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Ravichandran, Akshaya, Krutika Mahulikar, Shreya Agarwal, and Suresh Sankaranarayanan. "Post Thoracic Surgery Life Expectancy Prediction Using Machine Learning." International Journal of Healthcare Information Systems and Informatics 16, no. 4 (2021): 1–20. http://dx.doi.org/10.4018/ijhisi.20211001.oa32.

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Lung cancer survival rate is very limited post-surgery irrespective it is “small cell and non-small cell”. Lot of work have been carried out by employing machine learning in life expectancy prediction post thoracic surgery for patients with lung cancer. Many machine learning models like Multi-layer perceptron (MLP), SVM, Naïve Bayes, Decision Tree, Random forest, Logistic regression been applied for post thoracic surgery life expectancy prediction based on data sets from UCI. Also, work has been carried out towards attribute ranking and selection in performing better in improving prediction ac
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Meagher, Timothy. "Predicting Life Expectancy: Precise Science or Fool's Errand?" Journal of Insurance Medicine 48, no. 1 (2019): 1–4. http://dx.doi.org/10.17849/insm-48-1-1-4.1.

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Dissertations / Theses on the topic "Predicting life expectancy"

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Hasan, Md Saeed, and mdsaeed hasan@rmit edu au. "Predicting Life Expectancy of Concrete Septic Tanks Exposed to Sulphate and Biogenic Sulphuric Acid Attack." RMIT University. Civil, Environmental and Chemical Engineering, 2009. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20091217.102006.

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The prediction of the expected long-term performance of concrete exposed to sewage and similar materials can be difficult as it is affected by a large number of parameters. In addition, the deterioration process in concrete is generally slow. The focus of the study was to ascertain the life expectancy of concrete septic tanks located in rural Victoria. In developing the accelerated test method, ASTM C 192, ASTM C 452, ASTM C 1293 and ASTM C 109 standard procedures were adopted wherever possible. From the analysis of mass change data after 350 days, it was found that the mass change rate fo
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Gaspari, Andrea. "The durability of timber buildings: a decay prediction model to estimate the life expectancy of timber structures." Doctoral thesis, Università degli studi di Trento, 2022. https://hdl.handle.net/11572/355244.

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The aim of this research work is to develop reliable strategies to assess the durability of timber structures investigating the natural hazards affecting the safety and the life-expectancy of timber buildings. From an all encompassing point of view, the life-expectancy of timber buildings was predicted considering the effects of a fungal attack on the durability of a timber structural element. The prediction of life-expectancy of timber buildings was set up through a risk-based approach consisting of (i) the analysis of the state of the art, (ii) the definition of risk classes and decision tr
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Santos, Hellen Geremias dos. "Comparação da performance de algoritmos de machine learning para a análise preditiva em saúde pública e medicina." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/6/6141/tde-09102018-132826/.

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Modelos preditivos estimam o risco de eventos ou agravos relacionados à saúde e podem ser utilizados como ferramenta auxiliar em tomadas de decisão por gestores e profissionais de saúde. Algoritmos de machine learning (ML), por sua vez, apresentam potencial para identificar relações complexas e não-lineares presentes nos dados, com consequências positivas na performance preditiva desses modelos. A presente pesquisa objetivou aplicar técnicas supervisionadas de ML e comparar sua performance em problemas de classificação e de regressão para predizer respostas de interesse para a saúde pública e
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Fetzek, Charles A. "Behavior-based power management in autonomous mobile robots." Wright-Patterson AFB : Air Force Institute of Technology, 2008. http://handle.dtic.mil/100.2/ADA487084.

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Helmersson, Madeleine. "Annuity Divisors." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-138767.

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This paper studies the differences and similarities between the discrete annuity divisor of the income pension compared to the continuous annuity divisor of the premium pension in Sweden. First discrete and continuous annuity divisors are compared and found to be equivalent given the same underlying mortality. The income divisor is based on observed mortality in a period setting while the premium divisor which is based on projected mortality in a cohort setting. The expected performance of the two methods is studied by constructing prediction intervals based on Lee-Carter models with either a
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Horníková, Andrea. "Analýza kohortní úmrtnosti ve vysokých věcích." Master's thesis, Vysoká škola ekonomická v Praze, 2016. http://www.nusl.cz/ntk/nusl-205509.

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The objective of this thesis is to find patterns trends and assumptions for mortality vs. age prediction. Based on the analysis of trends in the already extinct cohorts, the most suitable models for estimating the future development of mortality among surviving cohorts are selected. This thesis compares real data extinct cohorts with balanced data Gompertz-Makehamovy function. The research and analysis is focused on the specifics of cohort mortality from the age of 90. The last part of this thesis illustrates comparison between real data of extinct cohorts with DeRaS model outputs. The selecti
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Hsiao, Chien-Lung, and 蕭建龍. "The Study on First line Soccer Players’ Expectancy-Value Belief to the Prediction of Athlete Burnout in Taipei and New Taipei." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/t83pq8.

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碩士<br>佛光大學<br>未來與樂活產業學系<br>103<br>The subjects of this study were from Taipei and New Taipei City. The purpose of this investigation to examine the prediction and correlation between the expectancy-value belief and the burnout of soccer players with different demographic background. The 394 participants were county-level players attained soccer games in Taipei and New Taipei City in 2014. Questionnaires were used for gathering data and the data was statistically analyzed and discussed. The results were as follows: 1. Male elementary students are a large majority among the participants. They ha
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Books on the topic "Predicting life expectancy"

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Wolk, Gloria Grening. Viatical & life settlements: An investor's guide. BIALKIN BOOKS, 2004.

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National Institutes of Health (U.S.), ed. Life expectancy in G-7 industrialized nations may exceed past predictions, study suggests. the National Institute on Aging, 2000.

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M, Seltzer Mildred, ed. The Impact of increased life expectancy: Beyond the gray horizon. Springer, 1995.

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Hurd, Michael D. The predictive validity of subjective probabilities of survival. National Bureau of Economic Research, 1997.

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Wolk, Gloria Grening. Viatical & Life Settlements: Viatical And Life Settlements (Wolk, Gloria Grening. Viatical Settlement.). Bialkin Books, 2005.

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International Conference on Gears 2017. VDI Verlag, 2017. http://dx.doi.org/10.51202/9783181022948.

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Talking about the design of modern high-performance power train applications, one of the essential components to focus on are the gears. Gears convert torque and speed in a very wide power range, at low cost and with minimal losses and noise emission. However, the demands regarding cost, power density, NVH-behavior and efficiency are steadily increasing. Demands, which can only be met using modern gearing technologies that allow combining individual materials, heat treatment and manufacturing processes. Particularly in the industrial sector, the requirements for the reliability and service lif
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O’Mahony, Constantinos. Hypertrophic cardiomyopathy: prevention of sudden cardiac death. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198784906.003.0354.

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Sudden cardiac death (SCD) secondary to ventricular arrhythmias is the most common mode of death in hypertrophic cardiomyopathy (HCM) and can be effectively prevented with an implantable cardioverter defibrillator (ICD). The risk of SCD in HCM relates to the severity of the phenotype and regular risk stratification is an integral part of routine clinical care. For the primary prevention of SCD, risk stratification involves the assessment of seven readily available clinical parameters (age, maximal left ventricular wall thickness, left atrial diameter, left ventricular outflow tract gradient, n
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Book chapters on the topic "Predicting life expectancy"

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Tuj Jannat, Fatema, Khalid Been Md Badruzzaman Biplob, and Abu Kowshir Bitto. "Predicting Bangladesh Life Expectancy Using Multiple Depend Features and Regression Models." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0047-3_5.

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Sekhar, B. V. D. S., Ahmed Alkhayyat, Manisha Mittal, Sanjeev Kumar Shah, and Rajan Verma. "Design and Implementation of a Multi-variable Statistical Analysis Model for Predicting Socioeconomic Impacts on People’s Life Expectancy." In Smart Innovation, Systems and Technologies. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-0139-4_39.

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Amit, Reshov Roy, Rajesh Tanwar, and Vikram Singh. "Evaluating Models for Better Life Expectancy Prediction." In Computational Intelligence and Data Analytics. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3391-2_30.

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Ansari, Needa, and Samir Patel. "Prediction of Life Expectancy for India Using Time Series Models." In Communications in Computer and Information Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-88042-1_21.

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Keilman, Nico, and Sigve Kristoffersen. "European Mortality Forecasts: Are the Targets Still Moving?" In Developments in Demographic Forecasting. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42472-5_9.

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Abstract Many statistical agencies routinely produce population forecasts, and revise these forecasts when new data become available, or when current demographic trends indicate that an update is necessary. When the forecaster strongly revises, from one forecast round to the next one, a forecast for a certain target year (for instance the life expectancy in 2050), this indicates large uncertainty connected to mortality predictions. The aim of this chapter is to shed more light on the uncertainty in mortality forecasts, by analysing the extent to which life expectancy predictions for 2030 and 2
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George, Anna Merine, Anudeep Nagaraja, L. Ananth Naik, and J. Naresh. "An IoT Framework for Healthcare Monitoring and Machine Learning for Life Expectancy Prediction." In Evolutionary Computing and Mobile Sustainable Networks. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5258-8_59.

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Polash, Md Shohidul Islam, Shazzad Hossen, and Aminul Haque. "Five-Year Life Expectancy Prediction of Prostate Cancer Patients Using Machine Learning Algorithms." In Soft Computing and Its Engineering Applications. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27609-5_25.

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Kumar, K. Manoj, and Kennedy Babu C. Nelson. "Life expectancy prediction of electronic items using artificial neural networks algorithm compared with ridge logistic regression algorithm for improved accuracy." In Recent Innovations in Sciences and Humanities. CRC Press, 2025. https://doi.org/10.1201/9781003606611-45.

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Rajput, Vije Kumar, Jack Dowie, and Mette Kjer Kaltoft. "Individualising Life Expectancy Is Necessary for Optimal Prescribing." In Studies in Health Technology and Informatics. IOS Press, 2022. http://dx.doi.org/10.3233/shti220918.

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One possible cause of overprescribing (or insufficient deprescribing) is the failure to explicitly address the individual’s life expectancy (LE). For example, if a LE estimate shows the person has six months to live, this should influence the prescribing of a medication that offers benefits only over a much longer LE. Predicting exactly the number of years a person will live is impossible, but probabilistic forecasting is possible and arguably essential, both for the selection of the optimal intervention and for meeting the ‘reasonable patient’ standard of information about the harms and benef
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Broughton, William R., and Antony S. Maxwell. "Accelerated Life Testing and Aging." In Characterization and Failure Analysis of Plastics. ASM International, 2022. http://dx.doi.org/10.31399/asm.hb.v11a.a0006909.

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Abstract Accelerated life testing and aging methodologies are increasingly being used to generate engineering data for determining material property degradation and service life (or fitness for purpose) of plastic materials for hostile service conditions. This article presents an overview of accelerated life testing and aging of unreinforced and fiber-reinforced plastic materials for assessing long-term material properties and life expectancy in hostile service environments. It considers various environmental factors, such as temperature, humidity, pressure, weathering, liquid chemicals (i.e.,
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Conference papers on the topic "Predicting life expectancy"

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D, Anu, Jayanth S, and Mehak Nasheen Aslam. "Predicting Life Expectancy with Astrological Factors and Machine Learning." In 2024 Third International Conference on Artificial Intelligence, Computational Electronics and Communication System (AICECS). IEEE, 2024. https://doi.org/10.1109/aicecs63354.2024.10957658.

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Ahmed, Marzia, Abu Kowshir Bitto, Md Maruf Hassan, and Touhid Bhuiyan. "Predicting Life Expectancy Using Stacking Regressor Models: Analyzing the Impact of GDP and Population Dynamics." In 2025 International Conference on Electrical, Computer and Communication Engineering (ECCE). IEEE, 2025. https://doi.org/10.1109/ecce64574.2025.11013274.

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Yousuf Ali, Md Nawab, Omar Faruq, Fahad Ahammed, Kazi Mahzabin, Shahriar Sadman Dihan, and Israt Jahan. "Predicting Post-Thoracic Surgery Life Expectancy for Lung Cancer Using Machine Learning with SHapley Additive exPlanations." In 2024 27th International Conference on Computer and Information Technology (ICCIT). IEEE, 2024. https://doi.org/10.1109/iccit64611.2024.11022499.

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Jahanian, Shahriar, and Jamshid Goshtasbi-G. "On the Reliability Analysis of VLSI Chips When Subjected to Thermal Cycling." In ASME 1997 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/imece1997-1353.

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Abstract Elevated temperature has been considered as a dominant factor of stress which lowers the reliability and life expectancy of the microelectronics devices. Arrhenius model is commonly used for predicting the reliability and failure rate of the microelectronics devices as a function of ambient temperature. Arrhenuis model extrapolates life data, obtained from units tested at constant elevated temperatures, to the working temperatures. Generally, the temperature of microelectronics devices are lowered using an appropriate cooling method to achieve a desired reliability and life expectancy
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Nouri, Mahdi, Jafar Mesbah, and Soheil B. Shaibani. "A Verified Computer Model for Corrosion Rate Prediction in a Di-Ethanol Amine System Using Field Data." In CORROSION 2008. NACE International, 2008. https://doi.org/10.5006/c2008-08417.

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Abstract Many parameters affect corrosion rate significantly such as operating temperature, CO2 and H2S partial pressure, CO2 and H2S ratio, type of process fluid, dissolved chlorides, pH, operating conditions, scaling tendency of corrosion products, oil wetting, type of corrosion inhibitor used and its efficiency, flow velocity of gas phase and/or multiphase systems, and material of construction. The purpose of this paper is to demonstrate the effect of the parameters and application of methods predicting corrosion rate in gas treating plants using DEA (Di-Ethanol Amine) aqueous solution. A c
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Narooka, Preeti, Aarushi Vashistha, Priyanka Mitra, and Gulisha Derashri. "Life Expectancy Prediction using Machine Learning Technique – KNN." In 2024 IEEE 3rd World Conference on Applied Intelligence and Computing (AIC). IEEE, 2024. http://dx.doi.org/10.1109/aic61668.2024.10730995.

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Ozsahin, Dilber Uzun, Declan Ikechukwu Emegano, Leena R. David, Abir Jaafar Hussain, Berna Uzun, and Ilker Ozsahin. "Global Life Expectancy Prediction Using Machine Learning Ensemble Techniques." In 2024 17th International Conference on Development in eSystem Engineering (DeSE). IEEE, 2024. https://doi.org/10.1109/dese63988.2024.10912031.

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Choudhury, Tamanna, Shivam Kumar Bharti, Mahendra Kumar Gourisaria, Junali Jasmine Jena, Dayal Kumar Behera, and Anjan Bandyopadhyay. "Predictive Modeling of Life Expectancy Using Machine Learning Algorithms." In 2024 Global Conference on Communications and Information Technologies (GCCIT). IEEE, 2024. https://doi.org/10.1109/gccit63234.2024.10862085.

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T S, Pranjal, Srijan Badhya, Neha Reddy, Srikrishna B, and Priya Badrinath. "Healthy Life Expectancy (HALE) Analysis and Prediction using Machine Learning." In 2025 International Conference on Artificial Intelligence and Data Engineering (AIDE). IEEE, 2025. https://doi.org/10.1109/aide64228.2025.10987496.

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Navarro, M. "Life Time Prediction of Cross Linked Polypropylene Coatings." In CORROSION 2016. NACE International, 2016. https://doi.org/10.5006/c2016-07742.

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Abstract Heat Shrink Sleeve (HSS) coatings technology is based on radiation cross-linking of Polyethylene and Polypropylene sheets in combination with multiple types of adhesive chemistries. Heat Shrink sleeves have been and continue being used for the corrosion protection of Oil, Gas, Water and District Heating pipelines. This paper addresses the laboratory studies of the long term thermal, oxidative and hydrolytic stability of radiation cross-linked polyolefin as used in Heat Shrink Sleeves. Studies are presented on the results of long term heat aging and predicted life expectancy based upon
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Reports on the topic "Predicting life expectancy"

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Gupta, Shikhar, Mehtab Ahmed, Sayema ., Azam Haseen, and Saif Quaiser. Relevance of Preoperative Vessel Mapping and Early Postoperative Ultrasonography in Predicting AV Fistula Failure in Chronic Kidney Disease Patients. Science Repository, 2024. http://dx.doi.org/10.31487/j.rdi.2023.02.02.

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Introduction: The increasing prevalence of chronic kidney disease (CKD), coupled with advancements in the diagnosis and treatment of renal diseases and improvements in life expectancy, has led to a greater number of patients requiring hemodialysis. The preferred method of vascular access for hemodialysis is AV fistula formation; however, it is associated with a high rate of failure. In our prospective study, we focused on 40 CKD patients planned for initiation of maintenance hemodialysis. Methods: We employed preoperative ultrasound mapping to assess cephalic vein diameter, compressibility, an
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Keshav, Dr Geetha, Dr Suwaibah Fatima Samer, Dr Salman Haroon, and Dr Mohammed Abrar Hassan. TO STUDY THE CORRELATION OF BMI WITH ABO BLOOD GROUP AND CARDIOVASCULAR RISK AMONG MEDICAL STUDENTS. World Wide Journals, 2023. http://dx.doi.org/10.36106/ijar/2405523.

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Introduction: Advancements and increase in access to healthcare have increased the life expectancy in India from 32 years in 1947 to almost 70 years currently. Due to robust vaccination and basic health programs, most of the communicable diseases are kept under control. The disease burden is now skewed towards non-communicable diseases. It is an established fact that body mass index (BMI) is a reliable predictor of cardiovascular disease (CVD) later in life. Early prediction can decrease the disease load and enable early preventative measures. A more novel approach of connecting it with blood
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