Relevant bibliographies by topics / Risk prediction scores

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

Academic literature on the topic 'Risk prediction scores'

Author: Grafiati
Published: 4 June 2021
Last updated: 7 February 2022

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Journal articles on the topic "Risk prediction scores"

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Effraimidis, Grigoris. "MANAGEMENT OF ENDOCRINE DISEASE: Predictive scores in autoimmune thyroid disease: are they useful?" European Journal of Endocrinology 181, no. 3 (2019): R119—R131. http://dx.doi.org/10.1530/eje-19-0234.

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Prediction models are of a great assistance for predicting the development of a disease, detecting or screening undiagnosed patients, predicting the effectiveness of a treatment and helping toward better decision-making. Recently, three predictive scores in the field of autoimmune thyroid disease (AITD) have been introduced: The Thyroid Hormones Event Amsterdam (THEA) score: a predictive score of the development of overt AITD, the Graves’ Events After Therapy (GREAT) score: a prediction score for the risk of recurrence after antithyroid drugs withdrawal and the Prediction Graves’ Orbitopathy (
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Belialov, F. I. "RISK PREDICTION SCORES OF DISEASES." Complex Issues of Cardiovascular Diseases 7, no. 1 (2018): 84–93. http://dx.doi.org/10.17802/2306-1278-2018-7-1-84-93.

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Ridker, Paul M., and Nancy R. Cook. "Comparing Cardiovascular Risk Prediction Scores." Annals of Internal Medicine 162, no. 4 (2015): 313. http://dx.doi.org/10.7326/m14-2820.

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Banerjee, Amitava, Laurent Fauchier, Anne Bernard-Brunet, Nicolas Clementy, and Gregory Y. H. Lip. "Composite risk scores and composite endpoints in the risk prediction of outcomes in anticoagulated patients with atrial fibrillation." Thrombosis and Haemostasis 111, no. 03 (2014): 549–56. http://dx.doi.org/10.1160/th13-12-1033.

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SummarySeveral validated risk stratification schemes for prediction of ischaemic stroke (IS)/thromboembolism (TE) and major bleeding are available for patients with non-valvular atrial fibrillation (NVAF). On the basis for multiple common risk factors for IS/TE and bleeding, it has been suggested that composite risk prediction scores may be more practical and user-friendly than separate scores for bleeding and IS/TE. In a long-term prospective hospital registry of anticoagulated patients with newly diagnosed AF, we compared the predictive value of existing risk prediction scores as well as com
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Bäck, Caroline, Mads Hornum, Morten Buus Jørgensen, Ulver Spangsberg Lorenzen, Peter Skov Olsen, and Christian H. Møller. "Comprehensive assessment of frailty score supplements the existing cardiac surgical risk scores." European Journal of Cardio-Thoracic Surgery 60, no. 3 (2021): 710–16. http://dx.doi.org/10.1093/ejcts/ezab127.

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Abstract OBJECTIVES The commonly used cardiac surgery risk scores, European System for Cardiac Operative Risk Evaluation II and Society of Thoracic Surgeons score, are inaccurate in predicting mortality in the ageing patient population and do not include the biological age. This requests a need for a new risk score incorporating frailty. The aim of this study was to compare the prediction of mortality and the additive effect of comprehensive assessment of frailty score and the shortened version, frailty predicts death one year after elective cardiac surgery test on the existing risk scores. ME
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Pain, Oliver, Kylie P. Glanville, Saskia Hagenaars, et al. "Imputed gene expression risk scores: a functionally informed component of polygenic risk." Human Molecular Genetics 30, no. 8 (2021): 727–38. http://dx.doi.org/10.1093/hmg/ddab053.

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Abstract Integration of functional genomic annotations when estimating polygenic risk scores (PRS) can provide insight into aetiology and improve risk prediction. This study explores the predictive utility of gene expression risk scores (GeRS), calculated using imputed gene expression and transcriptome-wide association study (TWAS) results. The predictive utility of GeRS was evaluated using 12 neuropsychiatric and anthropometric outcomes measured in two target samples: UK Biobank and the Twins Early Development Study. GeRS were calculated based on imputed gene expression levels and TWAS result
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Lambert, Samuel A., Gad Abraham, and Michael Inouye. "Towards clinical utility of polygenic risk scores." Human Molecular Genetics 28, R2 (2019): R133—R142. http://dx.doi.org/10.1093/hmg/ddz187.

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Abstract Prediction of disease risk is an essential part of preventative medicine, often guiding clinical management. Risk prediction typically includes risk factors such as age, sex, family history of disease and lifestyle (e.g. smoking status); however, in recent years, there has been increasing interest to include genomic information into risk models. Polygenic risk scores (PRS) aggregate the effects of many genetic variants across the human genome into a single score and have recently been shown to have predictive value for multiple common diseases. In this review, we summarize the potenti
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Cosmin, Caraşca, Caraşca Emilian, Ţilea Ioan, Voidazan Septimiu, and Incze Alexandru. "Predictors of Postoperative Outcome in Patients with Lower Limb Surgical Revascularization." Acta Medica Marisiensis 62, no. 3 (2016): 313–17. http://dx.doi.org/10.1515/amma-2016-0037.

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AbstractObjective: In patients with critical limb ischemia who undergone revascularization procedures, the assessment of risk factors that may affect the postoperative outcome is of great importance. The main objective in this study is to assess the utility of two specific risk scores, the Finnvasc score and the modified Prevent III score.Methods: We evaluated the applicability of these two risk scores in 150 patients who undergone an unilateral infrainguinal surgical revascularization procedure. The receiver operating characteristic curve analysis was used to estimate the predictive value of
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Hu, Wei-Syun, and Cheng-Li Lin. "Comparison of CHA2DS2-VASc and C2HEST scores for predicting the incidence of atrial fibrillation among patients with end-stage renal disease." Perfusion 35, no. 8 (2020): 842–46. http://dx.doi.org/10.1177/0267659120930931.

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Purpose: The authors have studied assessment of CHA2DS2-VASc score versus C2HEST score in atrial fibrillation risk prediction in end-stage renal disease patients. Methods: The authors conducted this study by Longitudinal Health Insurance Database 2000. The authors totally enrolled 4,601 end-stage renal disease patients. The predictive capability of atrial fibrillation by using CHA2DS2-VASc and C2HEST score was estimated by area under the receiver operating characteristic curve (AUROC). Results: The AUROC for CHA2DS2-VASc score in predicting atrial fibrillation events was 0.5786, and AUROC for
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Ananthakrishnan, Ashwin N. "IBD risk prediction using multi-ethnic polygenic risk scores." Nature Reviews Gastroenterology & Hepatology 18, no. 4 (2021): 217–18. http://dx.doi.org/10.1038/s41575-021-00425-5.

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Dissertations / Theses on the topic "Risk prediction scores"

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Liew, Su May. "The impact of treatment and time on cardiovascular risk scores." Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:c7840ca1-f99a-472a-8a8b-aa7493504a3d.

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Cardiovascular risk scores predict an individual’s risk of developing cardiovascular disease. Many were developed and validated in study cohorts on risk-factor lowering treatment – a cause of inaccuracy. In addition, risk scores are criticised as being biased towards the elderly due to the prominence of age as a risk predictor. Although present guidelines advocate the use of short-term (5-10 year) absolute risk scores, other approaches to redress this perceived imbalance such as lifetime risk scores are being considered. The overall objective of this thesis is to identify the most appropriate
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Martínez, Millana Antonio. "ASSESSMENT OF RISK SCORES FOR THE PREDICTION AND DETECTION OF TYPE 2 DIABETES MELLITUS IN CLINICAL SETTINGS." Doctoral thesis, Universitat Politècnica de València, 2017. http://hdl.handle.net/10251/86209.

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Health and sociological indicators confirm that life expectancy is increasing, and so, the years that patients have to live with chronic diseases and co-morbidities. Type 2 Diabetes is one of the most common chronic diseases, specially linked to overweight and ages over sixty. As a metabolic disease, Type 2 Diabetes affects multiple organs by causing damage in blood vessels and nervous system at micro and macro scale. Mortality of subjects with diabetes is three times higher than the mortality for subjects with other chronic diseases. On the one hand, the management of diabetes is focused on
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Koechlin, Kathleen Marie. "Modeling childhood agricultural injury risk with composite measurement scales." Columbus, Ohio : Ohio State University, 2003. http://rave.ohiolink.edu/etdc/view?acc%5num=osu1064287970.

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Thesis (Ph. D.)--Ohio State University, 2003.<br>Title from first page of PDF file. Document formatted into pages; contains xxi, 308 p. : ill. (some col.). Advisor: J.R. Wilkins III, School of Public Health. Includes bibliographical references (p. 210-220).
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Shen, Hanyang, Bizu Gelaye, Hailiang Huang, Marta B. Rondon, Sixto Sanchez, and Laramie E. Duncan. "Polygenic prediction and GWAS of depression, PTSD, and suicidal ideation/self-harm in a Peruvian cohort." Springer Nature, 2020. http://hdl.handle.net/10757/652459.

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Genome-wide approaches including polygenic risk scores (PRSs) are now widely used in medical research; however, few studies have been conducted in low- and middle-income countries (LMICs), especially in South America. This study was designed to test the transferability of psychiatric PRSs to individuals with different ancestral and cultural backgrounds and to provide genome-wide association study (GWAS) results for psychiatric outcomes in this sample. The PrOMIS cohort (N = 3308) was recruited from prenatal care clinics at the Instituto Nacional Materno Perinatal (INMP) in Lima, Peru. Three ma
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Privé, Florian. "Genetic risk score based on statistical learning Efficient analysis of large-scale genome-wide data with two R packages: bigstatsr and bigsnpr Efficient implementation of penalized regression for genetic risk prediction Making the most of Clumping and Thresholding for polygenic scores." Thesis, Université Grenoble Alpes (ComUE), 2019. http://www.theses.fr/2019GREAS024.

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Le génotypage devient de moins en moins cher, rendant les données de génotypes disponibles pour des millions d’individus. Par ailleurs, l’imputation permet d’obtenir l’information génotypique pour des millions de positions de l’ADN, capturant l’essentiel de la variation génétique du génome humain. Compte tenu de la richesse des données et du fait que de nombreux traits et maladies sont héréditaires (par exemple, la génétique peut expliquer 80% de la variation de la taille dans la population), il est envisagé d’utiliser des modèles prédictifs basés sur l’information génétique dans le cadre d’un
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Rice, Janice. "Assessing Suicide Risk Scores as a Predictor of Suicidal Behaviors in a Correctional Psychiatric Facility." Antioch University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=antioch1438219998.

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Yan, Jia. "Using Genetic Information in Risk Prediction for Alcohol Dependence." VCU Scholars Compass, 2012. http://scholarscompass.vcu.edu/etd/2878.

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Family-based and genome-wide association studies (GWAS) of alcohol dependence (AD) have reported numerous associated variants. The clinical validity of these variants for predicting AD compared to family history has not yet been reported. These studies aim to explore the aggregate impact of multiple genetic variants with small effect sizes on risk prediction in order to provide a clinical interpretation of genetic contributions to AD. Data simulations showed that given AD’s prevalence and heritability, a risk prediction model incorporating all genetic contributions would have an area under the
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Wood, Anthony Paul. "The performance of insolvency prediction and credit risk models in the UK : a comparative study, development and wider application." Thesis, University of Exeter, 2012. http://hdl.handle.net/10036/4211.

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Contingent claims models have recently been applied to the field of corporate insolvency prediction in an attempt to provide the art with a theoretical methodology that has been lacking in the past. Limited studies have been carried out in order to empirically compare the performance of these “market” models with that of their accounting number-based counterparts. This thesis contributes to the literature in several ways: The thesis traces the evolution of the art of corporate insolvency prediction from its inception through to the present day, combining key developments and methodologies into
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Molnar, Amber. "Predicting Graft Loss Following Acute Kidney Injury in Patients With a Kidney Transplant." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/34236.

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Acute kidney injury (AKI), characterized by an abrupt loss of kidney function with retention of nitrogenous waste products, is common in the months to years following kidney transplantation and is associated with an increased risk of transplant failure (graft loss). Kidney transplant patients who experience graft loss and return to dialysis have an increased mortality risk and a lower quality of life. Research involving kidney transplant patients can prove challenging, as they are relatively small in number. To increase statistical power, researchers may utilize administrative databases. Howev
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Lluís, Ganella Carla 1984. "Genetic factors associated with coronary heart disease and analysis of their predictive capacity." Doctoral thesis, Universitat Pompeu Fabra, 2012. http://hdl.handle.net/10803/84185.

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The main expansion of the discovery of genetic variants associated with complex diseases has occurred during the last decade. This expansion has been accompanied, and in some sense motivated, by the desire to use this information to improve the predictive capacity of many diseases with an unidentified familial component, including coronary heart disease (CHD), with the aim of translating this genetic knowledge into clinical practice. This doctoral thesis is structured in two lines of investigation that address distinct aspects of this issue, first to evaluate the possible role of genetic varia
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Books on the topic "Risk prediction scores"

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Wunsch, Hannah, and Andrew A. Kramer. The role and limitations of scoring systems. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0028.

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Scoring systems for critically-ill patients provide a measure of the severity of illness of patients admitted to intensive care units (ICUs). They are primarily based on patient characteristics, physiological derangement, and/or clinical assessments. Severity scores themselves allow for risk-adjusting outcomes, but they can also be used to provide a prediction of the overall risk of death, length of stay, or other outcome for critically ill patients. This allows for comparison of outcomes between different cohorts of patients or between observed and predicted ICU performance. There are a numbe
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Townsend, William M., and Emma C. Morris. ICU selection and outcome of patients with haematological malignancy. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0374.

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Patients with haematological malignancies require admission to the intensive care unit (ICU) due to the underlying disease, as a consequence of treatment with chemotherapy or after haematopoietic stem cell transplantation. With an increasing numbers of patients being diagnosed with these diseases and longer survival as treatments improve, the burden on ICU is anticipated to increase. There is compelling evidence that patients should not be denied admission to ICU based on the presence of a haematological malignancy. In this chapter the disease- and treatment-related reasons for ICU admission,
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Moreno, Rui. Organ failure scoring. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0030.

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The general outcome prediction models were not, by design, developed to track individual patients. They provided an indication of death risks for groups of ICU patients. Hence, investigators created organ failure scores. Instruments, such as Sequential Organ Failure Assessment (SOFA), Multiple Organ Dysfunction Score, or Logistic Organ Dysfunction Score are designed to evaluate separately the six most important organ systems in critically-ill patients sequentially, taken on a daily basis. Easy to perform, designed to be done at bedside, they do not forecast ICU or hospital mortality (apart fro
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Hage, Fadi G., Ayman Farag, and Gilbert J. Zoghbi. Screening Asymptomatic Subjects. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199392094.003.0016.

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Cardiovascular disease is the leading cause of death in the United States and accounts for more deaths than all cancers combined. Many apparently healthy adults first present to the health system with a myocardial infarction or sudden cardiac death. It is therefore imperative to assess the risk of cardiovascular events among currently asymptomatic individuals to try and intervene early in the disease process to prevent future events. Risk factors for the development of coronary artery disease in particular, and cardiovascular disease in general, have been identified from epidemiological studie
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Koczo, Agnes, Reshad Mahmud, and Belinda Rivera-Lebron. Pulmonary Embolism (DRAFT). Edited by Raghavan Murugan and Joseph M. Darby. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190612474.003.0020.

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This chapter examines the diagnosis, risk stratification, and breadth of treatment options for pulmonary embolism (PE). It reviews the decision pathways based on degree of clinical suspicion of PE and assessing pre-test probability using the Geneva and Wells’ Score. It also reviews the Pulmonary Embolism Rule-out Criteria (PERC) and D-dimer with high negative predictive values. Imaging and cardiac biomarkers, which allow classification and risk stratification of PE, are discussed in how they guide management. Options for parenteral anticoagulation including bridging to novel oral anticoagulant
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Arribas-Ayllon, Michael. Genetic Counseling in Psychiatry. Edited by John Z. Sadler, K. W. M. Fulford, and Werdie (C W. ). van Staden. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780198732372.013.54.

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This chapter offers a sober analysis of the history and prospects of genetic counseling in psychiatry. The present intersection of genetics and psychiatry is complex and limited in scope. The argument is made that recent genomic discoveries are unlikely to revolutionize genetic counseling because the complex nature of psychiatric conditions are not reducible to models of prediction. Susceptibility testing for psychiatric disorders is not a stable platform for clinical psychiatry because tests based on “common variation” are clinically unhelpful. Nevertheless, there are expectations that geneti
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Book chapters on the topic "Risk prediction scores"

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Akeh, Ugbah Paul, Steve Woolnough, and Olumide A. Olaniyan. "ECMWF Subseasonal to Seasonal Precipitation Forecast for Use as a Climate Adaptation Tool Over Nigeria." In African Handbook of Climate Change Adaptation. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-45106-6_97.

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AbstractFarmers in most parts of Africa and Asia still practice subsistence farming which relies minly on seasonal rainfall for Agricultural production. A timely and accurate prediction of the rainfall onset, cessation, expected rainfall amount, and its intra-seasonal variability is very likely to reduce losses and risk of extreme weather as well as maximize agricultural output to ensure food security.Based on this, a study was carried out to evaluate the performance of the European Centre for Medium-range Weather Forecast (ECMWF) numerical Weather Prediction Model and its Subseasonal to Seasonal (S2S) precipitation forecast to ascertain its usefulness as a climate change adaptation tool over Nigeria. Observed daily and monthly CHIRPS reanalysis precipitation amount and the ECMWF subseasonal weekly precipitation forecast data for the period 1995–2015 was used. The forecast and observed precipitation were analyzed from May to September while El Nino and La Nina years were identified using the Oceanic Nino Index. Skill of the forecast was determined from standard metrics: Bias, Root Mean Square Error (RMSE), and Anomaly Correlation Coefficient (ACC).The Bias, RMSE, and ACC scores reveal that the ECMWF model is capable of predicting precipitation over Southern Nigeria, with the best skill at one week lead time and poorest skills at lead time of 4 weeks. Results also show that the model is more reliable during El Nino years than La-Nina. However, some improvement in the model by ECMWF can give better results and make this tool a more dependable tool for disaster risk preparedness, reduction and prevention of possible damages and losses from extreme rainfall during the wet season, thus enhancing climate change adaptation.
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Rose, Sherri, Bruce Fireman, and Mark J. van der Laan. "Nested Case-Control Risk Score Prediction." In Targeted Learning. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-9782-1_15.

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Alenezi, Mamdouh, and Iman Almomani. "Empirical Analysis of Static Code Metrics for Predicting Risk Scores in Android Applications." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-78753-4_8.

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Amarbayasgalan, Tsatsral, Pham Van Huy, and Keun Ho Ryu. "Comparison of the Framingham Risk Score and Deep Neural Network-Based Coronary Heart Disease Risk Prediction." In Advances in Intelligent Information Hiding and Multimedia Signal Processing. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9714-1_30.

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Vuille, Jean-Claude, Claes Sundelin, and Tore Mellbin. "Predictive Value of a Combined Health Score at Four Years with Respect to Behavioral and Learning Problems at Age Ten." In Early Identification of Children at Risk. Springer US, 1985. http://dx.doi.org/10.1007/978-1-4899-0536-9_30.

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Manji, M., P. Gosling, and S. Brudney. "Early Identification Of High Risk Critically III Patients And Comparison With Acute Physiology Scores For Predicting Outcome." In Advances in Critical Care Testing. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18480-2_4.

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Galluccio, Carla, Rosa Fabbricatore, and Daniela Caso. "Exploring the intention to walk: a study on undergraduate students using item response theory and theory of planned behaviour." In Proceedings e report. Firenze University Press, 2021. http://dx.doi.org/10.36253/978-88-5518-304-8.30.

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Physical activity is one of the most basic human functions, and it is an important foundation of health throughout life. Physical activity apports benefit on both physical and mental health, reducing the risk of several diseases and lowering stress reactions, anxiety and depression. More specifically, physical activity is defined as "any bodily movement produced by skeletal muscles that require energy expenditure" (World Health Organization), including in this definition several activities. Among them, walking has been shown to improve physical and mental well-being in every age group. Despite that, insufficient walking among university students has been increasingly reported, requiring walking promotion intervention. In order to do this, dividing students based on their intention to walk might be useful since the intention is considered as the best predictor of behaviour. In this work, we carried out a study on university students' intention to walk and some of its predictors by exploiting Item Response Theory (IRT) models. In particular, we inspected the predictors of intention by mean of Rating Scale Graded Response Model (RS-GRM). Then we used the Latent Class IRT model to divide students according to their intention to walk, including predictors' scores as covariates. We chose the intention's predictors according to an extension of the Theory of Planned Behaviour (TPB), with both classic and additional variables. The formers are attitude toward behaviour, subjective norms, and perceived behavioural control, whereas we used risk perception, self-efficacy, anticipation, self-identity and anticipated regret as additional variables. Data was collected administrating a self-report questionnaire to undergraduate students enrolled in the Psychology course at Federico II University of Naples.
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Kallarakkal, Jain, and PB Jayagopal. "ACS Risk Prediction Scores: Which to Follow?" In CSI: Cardiology Update 2015 (2 Volumes). Jaypee Brothers Medical Publishers (P) Ltd., 2016. http://dx.doi.org/10.5005/jp/books/12785_35.

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Duceppe, Emmanuelle, and P. J. Devereaux. "Preoperative evaluation: biomarkers." In ESC CardioMed, edited by Steen Kristensen. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198784906.003.0634.

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It is estimated that over 200 million major surgeries are performed worldwide annually, of which more than 10 million patients will suffer a major cardiac complication. Accurate preoperative cardiac risk estimation is important to allow patients to make informed decisions regarding surgery and to identify patients who require enhanced monitoring after surgery. Physicians primarily use clinical evaluation to assess preoperative cardiac risk, and often clinicians use clinical risk scores. Although such scores have utility, these clinical risk scores often underestimate perioperative cardiac risk. Biomarkers further enhance risk prediction; tests can be performed quickly with limited costs, with results readily available during initial preoperative evaluation. The predictive capabilities of several biomarkers have been studied in non-cardiac surgery. N-terminal pro-brain natriuretic peptide (NT-proBNP) and BNP have the most robust evidence supporting their use to enhance prediction of perioperative major cardiac events.
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Adler, Amanda I., and Simon Griffin. "Prediction models for cardiovascular disease in diabetes mellitus." In Oxford Textbook of Endocrinology and Diabetes. Oxford University Press, 2011. http://dx.doi.org/10.1093/med/9780199235292.003.1544.

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Throughout the history of medicine, physicians have diagnosed and treated patients relying on their complaints and symptoms. Today, to gauge a patient’s risk of future ill health, physicians rely in addition on patient characteristics expressed as numerical values from physical and laboratory measurements, and from family and past medical histories. Risk scores represent examples of mathematical equations that utilize this information to model reality. Although sometimes not recognized as such, models currently aid in the everyday care of patients with diabetes and include, for example, simple models for adiposity (e.g. body mass index), more complex models for glomerular function, and even more complex algorithms to calculate dosages for continuous subcutaneous insulin based on levels of blood glucose, insulin sensitivity, exercise, diet, and more. Calculators such as the Framingham or United Kingdom Prospective Diabetes Study (UKPDS) risk equations are increasingly being used to predict the occurrence of cardiovascular disease (CVD) and death. Among the complications of diabetes, CVD, comprising cerebrovascular, coronary, and depending on the definition, peripheral arterial disease, occurs most frequently and generates the highest costs. Cardiovascular risk scores provide a numerical estimate of the risk of future CVD and death from CVD, conditional on the presence of a number of factors.
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Conference papers on the topic "Risk prediction scores"

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Uckun, S. "Abstract P5-12-16: Combinatorial risk scores: Personalized multi-omic prediction of disease risk." In Abstracts: 2018 San Antonio Breast Cancer Symposium; December 4-8, 2018; San Antonio, Texas. American Association for Cancer Research, 2019. http://dx.doi.org/10.1158/1538-7445.sabcs18-p5-12-16.

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Kleinstern, Geffen, Dennis Robinson, Tim G. Call, et al. "Abstract A06: Association of environmental risk factors, family history, and polygenic risk scores with chronic lymphocytic leukemia." In Abstracts: AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; November 16-19, 2016; Orlando, FL. American Association for Cancer Research, 2017. http://dx.doi.org/10.1158/1538-7755.carisk16-a06.

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Kleinstern, Geffen, Dennis Robinson, Tim G. Call, et al. "Abstract PR03: Association of environmental risk factors, family history, and polygenic risk scores with chronic lymphocytic leukemia." In Abstracts: AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; November 16-19, 2016; Orlando, FL. American Association for Cancer Research, 2017. http://dx.doi.org/10.1158/1538-7755.carisk16-pr03.

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Kachuri, Linda, Rebecca E. Graff, Karl Smith-Byrne, et al. "Abstract 2319: Pan-cancer analysis of polygenic risk scores reveals improvement in risk prediction and stratification." In Proceedings: AACR Annual Meeting 2020; April 27-28, 2020 and June 22-24, 2020; Philadelphia, PA. American Association for Cancer Research, 2020. http://dx.doi.org/10.1158/1538-7445.am2020-2319.

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"Evaluation of Published Clinical Scores for the Prediction of Cardiometabolic Risk in the SEMEOTICONS Project." In Special Session on Signals and Signs Understanding for Personalized Guidance to Promote Healthy Lifestyles. SCITEPRESS - Science and and Technology Publications, 2014. http://dx.doi.org/10.5220/0004939005990605.

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Wang, Louise, Heena Desai, Anh Le, et al. "Abstract LB222: Performance of polygenic risk scores for GI cancer prediction in an academic biobank." In Proceedings: AACR Annual Meeting 2021; April 10-15, 2021 and May 17-21, 2021; Philadelphia, PA. American Association for Cancer Research, 2021. http://dx.doi.org/10.1158/1538-7445.am2021-lb222.

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Rouis, Houda, Hela Kamoun, Hadhemi Rjeb, et al. "Comparison of risk prediction scores for venous thromboembolism in lung cancer patients: a retrospective cohort study." In ERS International Congress 2019 abstracts. European Respiratory Society, 2019. http://dx.doi.org/10.1183/13993003.congress-2019.pa4659.

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Kerr, B., L. Brandon, V. O’Sullivan, et al. "5 Clinical prediction scores with or without NTproBNP in predicting stroke and transient ischemic attack in at-risk patients without atrial fibrillation – the stop-HF experience." In Irish Cardiac Society Annual Scientific Meeting & AGM (Virtual), October 1st – 3rd 2020. BMJ Publishing Group Ltd and British Cardiovascular Society, 2020. http://dx.doi.org/10.1136/heartjnl-2020-ics.5.

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Kara, Mustafa Can, Malina Majeran, Bret Peterson, Tom Wimberly, and Greg Sinclair. "A Machine Learning Workflow to Predict Anomalous Sanding Events in Deepwater Wells." In Offshore Technology Conference. OTC, 2021. http://dx.doi.org/10.4043/31234-ms.

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Abstract Deepwater wells possess a high risk of sand escaping the reservoir into the production systems. Sand production is a common operational issue which results in potential equipment damage and hence product contamination. Excessive sand erosion causes blockage in tubulars and cavities in downhole equipment (subsea valves, chokes, bends etc.), resulting in maintenance costs for subsea equipment that adds up to millions of dollars yearly to operators. In this work, a scalable Machine Learning (ML) model readily accessing historical and real-time feed of sensor and simulation data is built
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Aprillia, Happy, Hong-Tzer Yang, and Chao-Ming Huang. "Probabilistic Load Prediction with Risk-Severity Score." In IECON 2020 - 46th Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2020. http://dx.doi.org/10.1109/iecon43393.2020.9255342.

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Reports on the topic "Risk prediction scores"

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Dy, Sydney M., Julie M. Waldfogel, Danetta H. Sloan, et al. Integrating Palliative Care in Ambulatory Care of Noncancer Serious Chronic Illness: A Systematic Review. Agency for Healthcare Research and Quality (AHRQ), 2020. http://dx.doi.org/10.23970/ahrqepccer237.

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Objectives. To evaluate availability, effectiveness, and implementation of interventions for integrating palliative care into ambulatory care for U.S.-based adults with serious life-threatening chronic illness or conditions other than cancer and their caregivers We evaluated interventions addressing identification of patients, patient and caregiver education, shared decision-making tools, clinician education, and models of care. Data sources. We searched key U.S. national websites (March 2020) and PubMed®, CINAHL®, and the Cochrane Central Register of Controlled Trials (through May 2020). We a
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Halker Singh, Rashmi B., Juliana H. VanderPluym, Allison S. Morrow, et al. Acute Treatments for Episodic Migraine. Agency for Healthcare Research and Quality (AHRQ), 2020. http://dx.doi.org/10.23970/ahrqepccer239.

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Objectives. To evaluate the effectiveness and comparative effectiveness of pharmacologic and nonpharmacologic therapies for the acute treatment of episodic migraine in adults. Data sources. MEDLINE®, Embase®, Cochrane Central Registrar of Controlled Trials, Cochrane Database of Systematic Reviews, PsycINFO®, Scopus, and various grey literature sources from database inception to July 24, 2020. Comparative effectiveness evidence about triptans and nonsteroidal anti-inflammatory drugs (NSAIDs) was extracted from existing systematic reviews. Review methods. We included randomized controlled trials
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