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Books on the topic 'Prediction routing'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Morin, Kevin A. The use of routine monitoring data for assessment and prediction of water chemistry. s.n, 1993.

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2

Adam, Pintz, and United States. National Aeronautics and Space Administration., eds. Ceramic material life prediction: A program to translate ANSYS results to CARES/LIFE reliability analysis : final report. National Aeronautics and Space Administration, 1994.

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3

Wolsey, Thomas DeVere. Learning to predict and predicting to learn: Cognitive strategies and instructional routines. Pearson/Allyn & Bacon, 2009.

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4

Fund, Milbank Memorial, ed. Educated guesses: Making policy about medical screening tests. University of California Press, 1994.

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5

B, Friedman Richard, and Young Donald S, eds. Effects of disease on clinical laboratory tests. 3rd ed. AACC Press, 1997.

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6

B, Friedman Richard, ed. Effects of disease on clinical laboratory tests. 4th ed. AACC Press, 2001.

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7

Predicting Catastrophic BGP Routing Instabilities. Storming Media, 2004.

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8

Jones, Kent Leslie. An analysis of predictive adaptive routing in a HF packet radio network. 1994.

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9

The Characterization and Prediction of Soldier Performance During Routine Service and in Combat. Storming Media, 2002.

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10

Zastrau, David. Estimation of Uncertainty of Wind Energy Predictions: With Application to Weather Routing and Wind Power Generation. Lang GmbH, Internationaler Verlag der Wissenschaften, Peter, 2017.

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11

Zastrau, David. Estimation of Uncertainty of Wind Energy Predictions: With Application to Weather Routing and Wind Power Generation. Lang GmbH, Internationaler Verlag der Wissenschaften, Peter, 2017.

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12

Zastrau, David. Estimation of Uncertainty of Wind Energy Predictions: With Application to Weather Routing and Wind Power Generation. Lang GmbH, Internationaler Verlag der Wissenschaften, Peter, 2017.

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13

Zastrau, David. Estimation of Uncertainty of Wind Energy Predictions: With Application to Weather Routing and Wind Power Generation. Lang GmbH, Internationaler Verlag der Wissenschaften, Peter, 2017.

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14

Learning to Predict and Predicting to Learn: Cognitive Strategies and Instructional Routines. Prentice Hall, 2008.

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15

Krist, Alex H., and Vivian Jiang. Provider-Level Factors Influencing Implementation. Edited by David A. Chambers, Wynne E. Norton, and Cynthia A. Vinson. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190647421.003.0016.

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Cancer treatment is increasingly complex. The tools for diagnosis, staging, and predicting prognosis are rapidly evolving, as are the therapies, treatment modalities, and treatment protocols. The complexity of care, the need for a multidisciplinary team across settings, and patient-level factors all present providers with a unique set of challenges. The three case studies presented in this chapter explore strategies that help providers by (1) ensuring low-income patients with breast cancer receive care consistent with guidelines through patient engagement and navigation, (2) promoting and inco

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16

Kissane, David W. Psychosocial care of families in palliative care. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198806677.003.0007.

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The families of patients in the palliative care setting have a range of educational and care needs that form part of the basic responsibility of the hospice service. Routine family meetings are an important way to address these needs. Additionally, up to one third of families have some level of dysfunction in their relationships, which prove predictive of morbid bereavement outcomes—prolonged grief and major depressive disorders. These families who carry risk of poorer outcomes need additional care, optimally commenced during palliative care, and continued into bereavement to provide continuit

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17

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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18

Trinidad, Jose Eos. Subtle Webs. Oxford University PressNew York, NY, 2025. https://doi.org/10.1093/9780197786123.001.0001.

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Abstract Subtle Webs provides an unprecedented behind-the-scenes look at how local organizations in Chicago, Philadelphia, and New York City have transformed data and worked with schools to solve the problem of dropping out. In the process, the book reveals how organizations outside schools have created an invisible infrastructure not only to affect local school districts but also to shape US education. The book argues that changes in a decentralized system happen less through top-down policy mandates or bottom-up social movements and more through “outside-in” initiatives of networked organiza

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19

Turner, Neil, and Stewart Cameron. Proteinuria. Edited by Neil Turner. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199592548.003.0050.

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Excess protein in the urine almost always comes from the kidney. Proteinuria up to 150 mg/day in an adult (protein:creatinine ratio (PCR) up to 15 mg/mmol) is considered normal. Daily average excretion is 80 mg, of which about 30 mg is albumin that has been filtered and not reabsorbed. Other components comprise low-molecular-weight filtered proteins that have escaped reabsorption, and proteins secreted or lost into urine from cells of the nephron. Increased permeability of the glomerulus to high-molecular-weight proteins is the most common cause of the clinically detected proteinuria, and albu

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20

Friedman, Richard B., and Donald S. Young. Effects of Disease on Clinical Laboratory Tests (Effects Series). 3rd ed. American Association for Clinical Chemistry,, 1997.

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