Relevant bibliographies by topics / Health Shock Prediction

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

Academic literature on the topic 'Health Shock Prediction'

Author: Grafiati
Published: 4 June 2021
Last updated: 9 February 2022

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Journal articles on the topic "Health Shock Prediction"

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Fischer, G., A. Neurauter, L. Wieser, H. U. Strohmenger, and C. N. Nowak. "Prediction of Countershock Success." Methods of Information in Medicine 48, no. 05 (2009): 486–92. http://dx.doi.org/10.3414/me0580.

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Summary Objectives: Spectral analysis of the ventricular fibrillation (VF) ECG has been used for predicting countershock success, where the Fast Fourier Transformation (FFT) is the standard spectral estimator. Autoregressive (AR) spectral estimation should compute the spectrum with less computation time. This study compares the predictive power and computational performance of features obtained by the FFT and AR methods. Methods: In an animal model of VF cardiac arrest, 41 shocks were delivered in 25 swine. For feature parameter analysis, 2.5 s signal intervals directly before the shock and directly before the hands-off interval were used, respectively. Invasive recordings of the arterial pressure were used for assessing the outcome of each shock. For a proof of concept, a micro-controller program was implemented. Results: Calculating the area under the receiver operating characteristic (ROC) curve (AUC), the results of the AR-based features called spectral pole power (SPP) and spectral pole power with dominant frequency (DF) weighing (SPPDF) yield better outcome prediction results (85 %; 89 %) than common parameters based on FFT calculation method (centroid frequency (CF), amplitude spectrum area (AMSA)) (72%; 78%) during hands-off interval. Moreover, the predictive power of the feature parameters during ongoing CPR was not invalidated by closed-chest compressions. The calculation time of the AR-based parameters was nearly 2.5 times faster than the FFT-based features. Conclusion: Summing up, AR spectral estimators are an attractive option compared to FFT due to the reduced computational speed and the better outcome prediction. This might be of benefit when implementing AR prediction features on the microprocessor of a semi-automatic defibrillator.
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Sivaprasath, P., Raja Mookka Gounder, and B. Mythili. "Prediction of Shock by Peripheral Perfusion Index." Indian Journal of Pediatrics 86, no. 10 (June 13, 2019): 903–8. http://dx.doi.org/10.1007/s12098-019-02993-6.

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Thapa, Sameer, PN Prasad, and YM Shakya. "Serum Lactate Albumin Ratio as a Predictor of Mortality in Severe Sepsis and Septic Shock at Tribhuwan University Teaching Hospital, Kathmandu." Birat Journal of Health Sciences 2, no. 2 (November 2, 2017): 191–95. http://dx.doi.org/10.3126/bjhs.v2i2.18525.

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IntroductionSevere sepsis and septic shock, is a common cause of emergency room admission and is associated with high morbidity and mortality worldwide. This study inspects the prediction of mortality in severe sepsis and septic shock with increased lactate/albumin ratio.Objective The objective of the study was to predict the serum lactate albumin ratio as an indicator of mortality in severe sepsis and septic shock.MethodologyIt was a hospital based cross sectional study done at Tribhuvan University Teaching Hospital, Kathmandu from November 2015 to October 2016. The consent was taken from patients. Acute Physiology and Chronic Health Evaluation II score, serum lactate and serum albumin levels on first day of arrival in emergency room were calculated. Patients were classified as severe sepsis and septic shock and treated according to Surviving Sepsis Campaign 2012 guideline. The patient were follow up at 28 day, The associations of 28-day outcome with Acute Physiology and Chronic Health Evaluation II score, serum lactate value, serum albumin value and serum lactate albumin ratio value were derived.ResultsOut of total 240 severe sepsis and septic shock patients it is found that increased serum lactate/albumin ratio was an independent predictor of the mortality with cut off value of 0.07. Furthermore serum lactate albumin ratio shows strong correlation with APACHE 2 score in predicting mortality in severe sepsis and septic shock.ConclusionIncreased lactate/albumin ratio predicts mortality in patients with severe sepsis and septic shock. Birat Journal of Health Sciences Vol.2/No.1/Issue 2/ Jan - April 2017, Page: 191-195
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Ismail, Javed, and Jhuma Sankar. "Peripheral Perfusion Index – Magic Wand in Prediction of Shock?" Indian Journal of Pediatrics 86, no. 10 (July 13, 2019): 879–80. http://dx.doi.org/10.1007/s12098-019-03028-w.

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Miller, Robert J. H., Danielle Southern, Stephen B. Wilton, Matthew T. James, Bryan Har, Greg Schnell, Sean van Diepen, and Andrew D. M. Grant. "Comparative Prognostic Accuracy of Risk Prediction Models for Cardiogenic Shock." Journal of Intensive Care Medicine 35, no. 12 (October 14, 2019): 1513–19. http://dx.doi.org/10.1177/0885066619878125.

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Objectives: Despite advances in medical therapy, reperfusion, and mechanical support, cardiogenic shock remains associated with excess morbidity and mortality. Accurate risk stratification may improve patient management. We compared the accuracy of established risk scores for cardiogenic shock. Methods: Patients admitted to tertiary care center cardiac care units in the province of Alberta in 2015 were assessed for cardiogenic shock. The Acute Physiology and Chronic Health Evaluation-II (APACHE-II), CardShock, intra-aortic balloon pump (IABP) Shock II, and sepsis-related organ failure assessment (SOFA) risk scores were compared. Receiver operating characteristic curves were used to assess discrimination of in-hospital mortality and compared using DeLong’s method. Calibration was assessed using the Hosmer-Lemeshow goodness-of-fit test. Results: The study included 3021 patients, among whom 510 (16.9%) had cardiogenic shock. Patients with cardiogenic shock had longer median hospital stays (median 11.0 vs 4.1 days, P < .001) and were more likely to die (29.0% vs 2.5%, P < .001). All risk scores were adequately calibrated for predicting hospital morality except for the APACHE-II score (Hosmer-Lemeshow P < .001). Discrimination of in-hospital mortality with the APACHE-II (area under the curve [AUC]: 0.72, 95% confidence interval [CI]: 0.66-0.76) and IABP-Shock II (AUC: 0.73, 95% CI: 0.68-0.77) scores were similar, while the CardShock (AUC: 0.76, 95% CI: 0.72-0.81) and SOFA (AUC: 0.76, 95%CI: 0.72-0.81) scores had better discrimination for predicting in-hospital mortality. Conclusions: In a real-world population of patients with cardiogenic shock, existing risk scores had modest prognostic accuracy, with no clear superior score. Further investigation is required to improve the discriminative abilities of existing models or establish novel methods.
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Liberski, Piotr S., Michał Szewczyk, and Łukasz J. Krzych. "Haemogram-Derived Indices for Screening and Prognostication in Critically Ill Septic Shock Patients: A Case-Control Study." Diagnostics 10, no. 9 (August 27, 2020): 638. http://dx.doi.org/10.3390/diagnostics10090638.

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This study aimed (1) to assess the diagnostic accuracy of neutrophil-to-lymphocyte (NLR), platelet-to-lymphocyte (PLR), monocyte-to-lymphocyte (MLR) and platelet count-to-mean platelet volume (PLT/MPV) ratios in predicting septic shock in patients on admission to the intensive care unit (ICU) and (2) to compare it with the role of C-reactive protein (CRP), procalcitonin (PCT) and lactate level. We also sought (3) to verify whether the indices could be useful in ICU mortality prediction and (4) to compare them with Acute Physiology and Chronic Health Evaluation II (APACHE II), Simplified Acute Physiology Score II (SAPS II) and Sequential Organ Failure Assessment (SOFA) scores. This retrospective study covered 138 patients, including 61 subjects with multi-organ failure due to septic shock (study group) and 77 sex- and age-matched controls. Septic patients had significantly higher NLR (p < 0.01) and NLR predicted septic shock occurrence (area under the ROC curve, AUROC = 0.66; 95% CI 0.58–0.74). PLR, MLR and PLT/MPV were impractical in sepsis prediction. Combination of CRP with NLR improved septic shock prediction (AUROC = 0.88; 95% CI 0.81–0.93). All indices failed to predict ICU mortality. APACHE II and SAPS II predicted mortality with AUROC = 0.68; 95% CI 0.54–0.78 and AUROC = 0.7; 95% CI 0.57–0.81, respectively. High NLR may be useful to identify patients with multi-organ failure due to septic shock but should be interpreted along with CRP or PCT. The investigated indices are not related with mortality in this specific clinical setting.
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Thiel, Steven W., Jamie M. Rosini, William Shannon, Joshua A. Doherty, Scott T. Micek, and Marin H. Kollef. "Early prediction of septic shock in hospitalized patients." Journal of Hospital Medicine 5, no. 1 (January 2010): 19–25. http://dx.doi.org/10.1002/jhm.530.

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Vedy, Eric, and Frits van der Eerden. "Prediction of shock waves over a sound-absorbing area." Noise Control Engineering Journal 53, no. 3 (2005): 81. http://dx.doi.org/10.3397/1.2839247.

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Stanojevic, Sanja, Jenna Sykes, Anne L. Stephenson, Shawn D. Aaron, and George A. Whitmore. "Development and external validation of 1- and 2-year mortality prediction models in cystic fibrosis." European Respiratory Journal 54, no. 3 (May 16, 2019): 1900224. http://dx.doi.org/10.1183/13993003.00224-2019.

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IntroductionWe aimed to develop a clinical tool for predicting 1- and 2-year risk of death for patients with cystic fibrosis (CF). The model considers patients' overall health status as well as risk of intermittent shock events in calculating the risk of death.MethodsCanadian CF Registry data from 1982 to 2015 were used to develop a predictive risk model using threshold regression. A 2-year risk of death estimated conditional probability of surviving the second year given survival for the first year. UK CF Registry data from 2007 to 2013 were used to externally validate the model.ResultsThe combined effect of CF chronic health status and CF intermittent shock risk provided a simple clinical scoring tool for assessing 1-year and 2-year risk of death for an individual CF patient. At a threshold risk of death of ≥20%, the 1-year model had a sensitivity of 74% and specificity of 96%. The area under the receiver operating curve (AUC) for the 2-year mortality model was significantly greater than the AUC for a model that predicted survival based on forced expiratory volume in 1 s <30% predicted (AUC 0.95 versus 0.68 respectively, p<0.001). The Canadian-derived model validated well with the UK data and correctly identified 79% of deaths and 95% of survivors in a single year in the UK.ConclusionsThe prediction models provide an accurate risk of death over a 1- and 2-year time horizon. The models performed equally well when validated in an independent UK CF population.
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Sharma, Shruti, Abhishek Gupta, Sunil Kumar Virmani, and Ritesh Lal. "Assessment and comparison of 3 mortality prediction models SAPS II, APACHE II and SOFA for prediction of mortality in patients of sepsis." International Journal of Advances in Medicine 4, no. 3 (May 23, 2017): 623. http://dx.doi.org/10.18203/2349-3933.ijam20171476.

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Background: Little is known about outcomes of patients admitted to the ICU with severe sepsis and septic shock, despite the seriousness of sepsis as a public health problem in developing countries. Understanding sepsis outcome studies is hampered by lack of an agreed severity of illness scoring system for sepsis patients. The objective of the present study is to assess and compare the validity of 3 mortality prediction models SAPS 2, APACHE II and SOFA for prediction of mortality in patients of sepsis.Methods: One hundred patients of Sepsis were selected after applying the inclusion and exclusion criteria. Informed consent was taken from the patients or their relatives A careful and detailed history was recorded to assess the onset and duration of clinical events and the probable risk factors for the same; a detailed general physical examination was performed. Blood sampling for CBC, RFT, LFT and arterial blood gas analysis was done. SAPS 2, APACHE II and SOFA scores were calculated on the day of admission.Results: The ROC analysis shows that the best discrimination was provided by SAPS 2 score (AUROC=0.981), followed by APACHE II (AUROC=0.978) and SOFA (AUROC=0.911).Conclusions: SAPS 2 score was superior to the APACHE II and SOFA scores for predicting survival in patients with septic shock but a combination of factors must be taken in consideration to estimate the prognosis in the ICU.
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Dissertations / Theses on the topic "Health Shock Prediction"

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Mahmud, S. "Cloud enabled data analytics and visualization framework for health-shock prediction." Thesis, Coventry University, 2016. http://curve.coventry.ac.uk/open/items/deba667c-5142-4330-9fd0-c86db4a8c088/1.

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Health-shock can be defined as a health event that causes severe hardship to the household because of the financial burden for healthcare payments and the income loss due to inability to work. It is one of the most prevalent shocks faced by the people of underdeveloped and developing countries. In Pakistan especially, policy makers and healthcare sector face an uphill battle in dealing with health-shock due to the lack of a publicly available dataset and an effective data analytics approach. In order to address this problem, this thesis presents a data analytics and visualization framework for health-shock prediction based on a large-scale health informatics dataset. The framework is developed using cloud computing services based on Amazon web services integrated with Geographical Information Systems (GIS) to facilitate the capture, storage, indexing and visualization of big data for different stakeholders using smart devices. The data was collected through offline questionnaires and an online mobile based system through Begum Memhooda Welfare Trust (BMWT). All data was coded in the online system for the purpose of analysis and visualization. In order to develop a predictive model for health-shock, a user study was conducted to collect a multidimensional dataset from 1000 households in rural and remotely accessible regions of Pakistan, focusing on their health, access to health care facilities and social welfare, as well as economic and environmental factors. The collected data was used to generate a predictive model using a fuzzy rule summarization technique, which can provide stakeholders with interpretable linguistic rules to explain the causal factors affecting health-shock. The evaluation of the proposed system in terms of the interpretability and accuracy of the generated data models for classifying health-shock shows promising results. The prediction accuracy of the fuzzy model based on a k-fold crossvalidation of the data samples shows above 89% performance in predicting health-shock based on the given factors. Such a framework will not only help the government and policy makers to manage and mitigate health-shock effectively and timely, but will also provide a low-cost, flexible, scalable, and secure architecture for data analytics and visualization. Future work includes extending this study to form Pakistan’s first publicly available health informatics tool to help government and healthcare professionals to form policies and healthcare reforms. This study has implications at a national and international level to facilitate large-scale health data analytics through cloud computing in order to minimize the resource commitments needed to predict and manage health-shock.
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Mayaud, Louis. "Prediction of mortality in septic patients with hypotension." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:55a57418-de16-4932-8a42-af56bd380056.

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Sepsis remains the second largest killer in the Intensive Care Unit (ICU), giving rise to a significant economic burden ($17b per annum in the US, 0.3% of the gross domestic product). The aim of the work described in this thesis is to improve the estimation of severity in this population, with a view to improving the allocation of resources. A cohort of 2,143 adult patients with sepsis and hypotension was identified from the MIMIC-II database (v2.26). The implementation of state-of-the-art models confirms the superiority of the APACHE-IV model (AUC=73.3%) for mortality prediction using ICU admission data. Using the same subset of features, state-of-the art machine learning techniques (Support Vector Machines and Random Forests) give equivalent results. More recent mortality prediction models are also implemented and offer an improvement in discriminatory power (AUC=76.16%). A shift from expert-driven selection of variables to objective feature selection techniques using all available covariates leads to a major gain in performance (AUC=80.4%). A framework allowing simultaneous feature selection and parameter pruning is developed, using a genetic algorithm, and this offers similar performance. The model derived from the first 24 hours in the ICU is then compared with a “dynamic” model derived over the same time period, and this leads to a significant improvement in performance (AUC=82.7%). The study is then repeated using data surrounding the hypotensive episode in an attempt to capture the physiological response to hypotension and the effects of treatment. A significant increase in performance (AUC=85.3%) is obtained with the static model incorporating data both before and after the hypotensive episode. The equivalent dynamic model does not demonstrate a statistically significant improvement (AUC=85.6%). Testing on other ICU populations with sepsis is needed to validate the findings of this thesis, but the results presented in it highlight the role that data mining will increasingly play in clinical knowledge generation.
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Brito, Ema C. "Gene x lifestyle interactions in type 2 diabetes mellitus and related traits." Doctoral thesis, Umeå : Umeå University, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-30523.

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Sousa, Diana Natacha Quintal Faria de. "Shock Index as a predictor of outcome in children with septicshock." Dissertação, 2015. https://repositorio-aberto.up.pt/handle/10216/88810.

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Sousa, Diana Natacha Quintal Faria de. "Shock Index as a predictor of outcome in children with septicshock." Master's thesis, 2015. https://repositorio-aberto.up.pt/handle/10216/88810.

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Leal, Ana Isabel Vidal Ferreira. "Pediatric Shock Index as a predictor of outcome in children with traumatic brain injury admitted to PICU." Dissertação, 2018. https://repositorio-aberto.up.pt/handle/10216/112226.

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Leal, Ana Isabel Vidal Ferreira. "Pediatric Shock Index as a predictor of outcome in children with traumatic brain injury admitted to PICU." Master's thesis, 2018. https://hdl.handle.net/10216/112226.

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Books on the topic "Health Shock Prediction"

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Hope, Corman, and National Bureau of Economic Research., eds. Crime and circumstance: The effects of infant health shocks on fathers' criminal activity. Cambridge, Mass: National Bureau of Economic Research, 2006.

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Book chapters on the topic "Health Shock Prediction"

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Yokota, Y., Y. Kawamura, N. Matsumaru, and K. Shirai. "Septic Shock Prediction by Real Time Monitoring of Heart Rate Variability." In IFMBE Proceedings, 195–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23508-5_52.

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Diaz, Jose D. R., M. A. Díaz, N. C. Castro, B. Glover, G. Manoharan, and O. J. Escalona. "Use of Support Vector Machines in Predicting Success of Intracardiac Cardioversion by Electric Shocks in Patients with Atrial Fibrillation." In IV Latin American Congress on Biomedical Engineering 2007, Bioengineering Solutions for Latin America Health, 1168–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-74471-9_271.

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Kasimir-Bauer, S., H. Ottinger, P. Meusers, G. Brittinger, S. Seeber, and M. E. Scheulen. "In Acute Myeloid Leukemia only the Coexpression of at Least Two Proteins Including P-Glycoprotein, the Multidrug Resistance-Related Protein MRP, bcl-2, Mutant p53 and Heat-Shock Protein 27 is Predictive for the Response to Induction Chemotherapy." In Haematology and Blood Transfusion / Hämatologie und Bluttransfusion, 444–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-71960-8_57.

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Chew, Michelle S. "Septic shock." In Oxford Textbook of Advanced Critical Care Echocardiography, edited by Anthony McLean, Stephen Huang, and Andrew Hilton, 281–86. Oxford University Press, 2020. http://dx.doi.org/10.1093/med/9780198749288.003.0020.

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Failure or dysfunction of the cardiovascular system is the defining feature of septic shock. While there is now evidence for the central role of the heart in the pathophysiology of septic shock, it is important to remember that it is only one component of the cardiovascular system. Thus, it is often impossible to distinguish between the direct effects of sepsis on the heart and its responses to other changes in the cardiovascular system. Systolic, diastolic, left, and right heart functions are variably affected and are not mutually exclusive. They may be associated with rises in cardiac troponins and may be associated with underlying cardiovascular disease. Current evidence suggests left ventricular systolic dysfunction (assessed as reduced ejection fraction) is not associated with increased mortality, while diastolic dysfunction seems to be more predictive. Right heart failure occurs commonly, even with lung-protective ventilation strategies. Echocardiography is currently the only bedside technique providing comprehensive information regarding heart function during sepsis. In combination with information obtained with pulmonary arterial catheterization, it may be used to monitor the effects of fluid loading, mechanical ventilation, and vasopressor/inotropic therapy in the patient with septic shock. Future areas of research include (1) the development of a universal definition for septic cardiomyopathy; (2) investigating methods for distinguishing sepsis-specific changes from underlying disease; (3) investigating the relationship between cardiac biomarkers and echocardiographic changes; (4) investigating new echocardiographic markers of systolic and diastolic function; (5) integration of lung-protective mechanical ventilation and haemodynamic management strategies guided by echocardiographic findings.
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Fialho, André S., Federico Cismondi, Susana M. Vieira, Shane R. Reti, João M. C. Sousa, and Stan N. Finkelstein. "Challenges and Opportunities of Soft Computing Tools in Health Care Delivery." In Handbook of Research on ICTs and Management Systems for Improving Efficiency in Healthcare and Social Care, 321–40. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-3990-4.ch016.

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During the last decade, modern hospitals have witnessed a growth in the amount of information acquired, stored, and retrieved more than ever before. While aimed at helping healthcare personnel in providing care to patients, this high stream of data can also have a negative impact if not delivered in a simple and organized way. In this chapter, the authors explore the current opportunities and challenges that soft computing predictive tools face in healthcare delivery, and they then present an example of how some of these tools may contribute to the decision-making of health care providers for an important critical condition in Intensive Care Units (ICU)—septic shock. Despite current challenges, such as the availability of clean clinical data, accuracy, and interpretability, these systems will likely act to enhance the performance of a human expert and permit healthcare resources to be used more efficiently while maintaining or improving outcomes.
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Elhini, Maha Mohamed, and Dina Kafafy. "The Economic Impacts of COVID-19 on the Tourism Global Value Chain." In Handbook of Research on the Impacts and Implications of COVID-19 on the Tourism Industry, 92–114. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-8231-2.ch005.

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The purpose of this chapter is to examine the economic impacts of the COVID-19 pandemic on the tourism global value chain (GVC). Theoretical analysis revealed that being triggered by health factors, the coronavirus pandemic exerted an unprecedented shock on both the supply and demand sides of the tourism sector and the global economy. This resulted in implications that are more severe and less predictable than earlier crises that the world had witnessed. Analysis of the economic impact on various components of the tourism GVC revealed that measures adopted by world governments to protect their citizens resulted in massive damage to tourism related industries and to the global economy. The chapter concludes by predicting that the consequences of the current pandemic will inevitably give rise to new, more innovate tourism models, responding to the changing global economic and tourism landscape and to the change in consumers' characteristics and expectations.
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Slama, Michel, and Julien Maizel. "Pulmonary hypertension." In Oxford Textbook of Advanced Critical Care Echocardiography, edited by Anthony McLean, Stephen Huang, and Andrew Hilton, 133–40. Oxford University Press, 2020. http://dx.doi.org/10.1093/med/9780198749288.003.0009.

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Acute pulmonary hypertension (PH) is common in ICU patients, particularly in septic shock, acute respiratory distress syndrome (ARDS), pulmonary embolism, and cardiac heart failure. Although many patients with lung diseases develop chronic PH, primary pulmonary arterial hypertension is less frequent, but still can be observed in ICU patients. Pulmonary arterial pressure (PAP) can be assessed using continuous-wave Doppler with the help of colour Doppler. Tricuspid regurgitation can be recorded with systolic as well as mean PAP estimated respectively from maximal and mean velocity of flow. Excellent correlations with invasive methods were found despite PAP increasing with age, body mass, and arterial hypertension. Pulmonary regurgitation is useful to estimate diastolic, mean, and systolic PAP. The right ventricular outflow tract flow can be used to rule out or rule in PH. Also, isovolumic contraction time on tissue Doppler imaging (TDI) tricuspid annular velocities allows prediction of systolic PAP (sPAP). Chronic and acute PH are usually associated with dilation of the right ventricle, atrium, and inferior vena cava as well as paradoxical septal movement. Right ventricular hypertrophy, right ventricular systolic function, and the size of the left ventricle can help to differentiate chronic from acute PH.
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Nakatani, Satoshi. "Assist devices." In ESC CardioMed, edited by Frank Flachskampf, 454–56. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198784906.003.0093.

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Echocardiography is an indispensable tool in managing patients with an assist device. Before implantation, not only left ventricular but also right ventricular function should be evaluated because right ventricular dysfunction has a critical role in predicting outcomes. After implantation, echocardiography is used for optimization of an assist device settings and detecting possible complications such as right ventricular failure, progressive aortic regurgitation, and thrombosis. Pump malfunction causes changes in ventricular geometry and valve function which can be also detected by echocardiography. In some patients, left ventricular reverse remodelling occurs and an assist device can be weaned. Thus, follow-up of a patient after an assist device implantation with echocardiography is important. Mechanically, circulatory support with a ventricular assist device for end-stage heart failure or shock is a life-saving procedure. It is used for a bridge-to-recovery, a bridge-to-transplantation, or a destination therapy for those without an indication of transplantation and requires long-term support. The role of echocardiography in the management of patients with assist devices includes assessment of cardiac function, optimization of device settings, detection of complications, and evaluation of a possibility of weaning from a device.
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Tiber, Simon. "Upper and Lower Respiratory Tract Infections." In Tutorial Topics in Infection for the Combined Infection Training Programme. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198801740.003.0040.

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Pharyngitis is common with incidence peaking from autumn to spring. Respiratory viruses are most commonly implicated, and are generally self-limiting conditions not requiring diagnostic workup or treatment. Bacterial pharyngitis is less common, is spread by droplets or direct transmission, and Streptococcus pyogenes (Group A strep, or GAS) is the most frequent cause. Haemophilus influenzae, Mycoplasma pneumoniae, and Neisseria gonorrhoeae are less frequent causes. Rapid antigen detection tests make the point-of-care assessment of GAS pharyngitis possible, although a negative test does not exclude infection. No method can distinguish oropharyngeal colonization from actual infection, but culture can obtain antibiotic susceptibility testing. Suspicion of infection with Neisseria gonorrhoeae, Bordetella pertussis, Haemophilus influenzae, Mycoplasma pneumoniae, Chlamydophila pneumoniae, or Corynebacterium diptheriae should be communicated to the laboratory so that the appropriate culture media is utilized. The Centor criteria provide a clinical predictive score that can give the likelihood a sore throat is due to a bacterial infection with the following: the presence of tonsillar exudate, tender anterior cervical adenopathy, fever over 38°C, and absence of cough. If three or four of these criteria are met, the positive predictive value is 40% to 60%. The absence of three or four of the Centor criteria has a relatively high negative predictive value of 80%, and may be use to evaluate whether antibiotics can be withheld or deferred. Oral penicillin or macrolide are used to treat streptococcal pharyngitis. Treatment may reduce severity, duration, transmission, and risk of post-infectious sequelae like rheumatic heart disease and post-streptococcal glomerulonephritis. Other complications include scarlet fever, streptococcal toxic shock syndrome, and quinsy. Otitis media, is frequent in the young children, possibly due to a short and horizontal Eustachian tube. Purulent material buils up leading to a bulging, red tympanic membrane which may rupture and discharge. Intense local pain and fevers may occur. Streptococcus pneumoniae, Moraxella catarrhalis, and Haemophilus influenzae are frequently implicated. Frequently there are no sequelae, although complications include hearing impairment, and less common are mastoiditis, bacteraemia, and meningitis. Diagnosis is clinical based on presentation and otoscopic examination. Microbiological diagnosis is possible through culture of exuate on swab or following tympanocentesis.
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Conference papers on the topic "Health Shock Prediction"

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Kim, Yeo Jin, and Min Chi. "Temporal Belief Memory: Imputing Missing Data during RNN Training." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/322.

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We propose a bio-inspired approach named Temporal Belief Memory (TBM) for handling missing data with recurrent neural networks (RNNs). When modeling irregularly observed temporal sequences, conventional RNNs generally ignore the real-time intervals between consecutive observations. TBM is a missing value imputation method that considers the time continuity and captures latent missing patterns based on irregular real time intervals of the inputs. We evaluate our TBM approach with real-world electronic health records (EHRs) consisting of 52,919 visits and 4,224,567 events on a task of early prediction of septic shock. We compare TBM against multiple baselines including both domain experts' rules and the state-of-the-art missing data handling approach using both RNN and long-short term memory. The experimental results show that TBM outperforms all the competitive baseline approaches for the septic shock early prediction task.
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Zhang, Yuan, Xi Yang, Julie Ivy, and Min Chi. "ATTAIN: Attention-based Time-Aware LSTM Networks for Disease Progression Modeling." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/607.

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Modeling patient disease progression using Electronic Health Records (EHRs) is critical to assist clinical decision making. Long-Short Term Memory (LSTM) is an effective model to handle sequential data, such as EHRs, but it encounters two major limitations when applied to EHRs: it is unable to interpret the prediction results and it ignores the irregular time intervals between consecutive events. To tackle these limitations, we propose an attention-based time-aware LSTM Networks (ATTAIN), to improve the interpretability of LSTM and to identify the critical previous events for current diagnosis by modeling the inherent time irregularity. We validate ATTAIN on modeling the progression of an extremely challenging disease, septic shock, by using real-world EHRs. Our results demonstrate that the proposed framework outperforms the state-of-the-art models such as RETAIN and T-LSTM. Also, the generated interpretative time-aware attention weights shed some lights on the progression behaviors of septic shock.
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Ahmad, Rashidi, Mohamad Iqhbal Kunji, M. Zikri Ahmad, Meera Mohaideen Hj Abd Kareem, and Shamimi A. Halim. "Ultrasonographic abdominal aorta diameter changes: A predictor of hypovolemic shock class 1." In 2012 7th International Symposium on Health Informatics and Bioinformatics (HIBIT). IEEE, 2012. http://dx.doi.org/10.1109/hibit.2012.6209042.

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Billingsley, J. P., Mark Elert, Michael D. Furnish, Ricky Chau, Neil Holmes, and Jeffrey Nguyen. "FOX-7 SPECIFIC HEAT PREDICTION FROM A PROPOSED NOMINAL∕GENERIC SPECIFIC HEAT FOR CHNO ENERGETIC COMPOUNDS." In SHOCK COMPRESSION OF CONDENSED MATTER - 2007: Proceedings of the Conference of the American Physical Society Topical Group on Shock Compression of Condensed Matter. AIP, 2008. http://dx.doi.org/10.1063/1.2833270.

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Slimani, Jamel, and Pascale Kulisa. "Heat Transfer Computations for Turbine Blade Airfoils." In ASME 1996 Turbo Asia Conference. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/96-ta-008.

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The design and optimization of turbine blades subjected to high temperature flows require the prediction of aerodynamic and thermal flow characteristics. A computation of aerothermal viscous flow model has been developed suitable for the turbine blade design process. The computational time must be reduced to allow intensive use in an industrial framework. The physical model is based on a compressible boundary layer approach, and the turbulence is a one-equation model. Special attention has been paid to the influence of wall curvature on the turbulence modelling. Tests were performed on convex wall flows to validate the turbulence model. Turbine blade configurations were then computed. These tests include most difficulties that can be encountered in practice : laminar-turbulent transition, separation bubble, strong accelerations, shock wave. Satisfactory predictions of the wall heat transfer are observed.
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Lall, Pradeep, Dhananjay Panchagade, Prakriti Choudhary, Jeff Suhling, and Sameep Gupte. "Models for Shock and Vibration Survivability of Electronic and MEMS Packaging." In ASME 2005 Pacific Rim Technical Conference and Exhibition on Integration and Packaging of MEMS, NEMS, and Electronic Systems collocated with the ASME 2005 Heat Transfer Summer Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/ipack2005-73427.

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Product level assessment of drop and shock reliability relies heavily on experimental test methods. Prediction of drop and shock survivability is largely beyond the state-of-art. However, the use of experimental approach to test out every possible design variation, and identify the one that gives the maximum design margin is often not feasible because of product development cycle time and cost constraints. Presently, one of the primary methodologies for evaluating shock and vibration survivability of electronic packaging is the JEDEC drop test method, JESD22-B111 which tests board-level reliability of packaging. However, packages in electronic products may be subjected to a wide-array of boundary conditions beyond those targeted in the test method. In this paper, a failure-envelope approach based on wavelet transforms and damage proxies has been developed to model drop and shock survivability of electronic packaging. Data on damage progression under transient-shock and vibration in both 95.5Sn4.0Ag0.5Cu and 63Sn37Pb ball-grid arrays has been presented. Component types examined include — flex-substrate and rigid substrate ball-grid arrays. Dynamic measurements like acceleration, strain and resistance are measured and analyzed using high-speed data acquisition system capable of capturing in-situ strain, continuity and acceleration data in excess of 5 million samples per second. Ultra high-speed video at 150,000 fps per second has been used to capture the deformation kinematics. The concept of relative damage index has been used to both evaluate and predict damage progression during transient shock. The failure-envelope provides a fundamental basis for development of component integration guidelines to ensure survivability in shock and vibration environments at a user-specified confidence level. The approach is scalable to application at system-level. Explicit finite-element models have been developed for prediction of shock survivability based on the failure envelope. Model predictions have been correlated with experimental data for both leaded and leadfree ball-grid arrays.
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Waldrop, Michael, and Flint Thomas. "A Correction to the Barotropic Model of Gaseous Cavitation in Choked Converging-Diverging Nozzle Flows." In ASME 2020 Fluids Engineering Division Summer Meeting collocated with the ASME 2020 Heat Transfer Summer Conference and the ASME 2020 18th International Conference on Nanochannels, Microchannels, and Minichannels. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/fedsm2020-20301.

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Abstract The Barotropic Cavitation Model describes the behavior of a homogeneous mixture of liquid and gas bubbles (gaseous cavitation) as it traverses a converging-diverging (CD) nozzle. Its normal shock formulation makes reliable and accurate predictions of streamwise static pressure distribution from the nozzle inlet to just downstream of the throat and in the diverging section as the flow approaches the nozzle outlet. It fails in the intermediate portion of the divergence with maximum pressure prediction errors (as a fraction of nozzle inlet pressure) roughly equivalent to the back pressure ratio (as high as 0.46). A correction to the streamwise static pressure distributions predicted by the normal shock solution of the Barotropic Cavitation Model is proposed, applied and compared to experiments with aerated and non-aerated cavitation in several fluids. When used to simulate aerated cavitation of dodecane in a CD nozzle it predicts the location of first disagreement between the normal shock solution and experimental static pressure measurements within 4% of nozzle length. A polynomial curve fit between this predicted point (xcorr) and the normal shock location (xshock) then reduces maximum prediction error for static pressure in the correction region to no more than 0.11 (as a fraction of inlet pressure) for the aerated dodecane cases examined. For non-aerated gaseous cavitation in dodecane, water or JP8 jet fuel this error ratio does not exceed 0.13 and typical values are less than 0.07.
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Tallman, James A. "CFD Heat Transfer Predictions for a High-Pressure Turbine Stage." In ASME Turbo Expo 2004: Power for Land, Sea, and Air. ASMEDC, 2004. http://dx.doi.org/10.1115/gt2004-53654.

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Computational Fluid Dynamics (CFD) was used to predict the turbine airfoil heat transfer for the high-pressure vane and high-pressure blade of a modern, one and one half stage turbine at its correct scale. Airfoil pressure and heat transfer measurements were recently obtained for the turbine in a transient shock tunnel facility, which allows for the replication of the actual engine turbine’s design corrected speed, pressure ratio, and gas-to-metal temperature ratio. A 3-D, compressible, Reynolds-averaged Navier-Stokes CFD solver with k-ω turbulence modeling was used for the CFD predictions. The turbulence model’s implementation into the numerical procedure was modified slightly, in order to better capture the model’s intended near-wall behavior and resolve the heat transfer prediction. Both the high-pressure vane and high-pressure blade were computed as steady-state flows and for two different turbine Reynolds number settings. Overall, the predictions compare very favorably with the measurement for both pressure and heat transfer at the mid-span location. A discussion of the features of the airfoil heat transfer distribution is included.
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Lee, Min-Gyoo. "AERODYNAMIC HEATING PREDICTION OF REACTING BLUNT BODY FLOW WITH AN IMPINGING SHOCK WAVE." In International Heat Transfer Conference 11. Connecticut: Begellhouse, 1998. http://dx.doi.org/10.1615/ihtc11.3690.

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Roy, Subhajit, Bijaylakshmi Saikia, and Krishnendu Sinha. "Heat transfer prediction in shock-turbulent boundary layer interaction at flight enthalpy." In AIAA Scitech 2019 Forum. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2019. http://dx.doi.org/10.2514/6.2019-0339.

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