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Journal articles on the topic 'Treatment uncertainties'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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1

Chalmers, Sir Iain. "The uncertainties of treatment." Prescriber 21, no. 14 (2010): 7. http://dx.doi.org/10.1002/psb.652.

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2

WACHTER, KERRI. "Uncertainties Hinder IEED Treatment Options." Clinical Neurology News 3, no. 5 (2007): 18. https://doi.org/10.1016/s1553-3212(07)70164-4.

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3

Belia, E., Y. Amerlinck, L. Benedetti, et al. "Wastewater treatment modelling: dealing with uncertainties." Water Science and Technology 60, no. 8 (2009): 1929–41. http://dx.doi.org/10.2166/wst.2009.225.

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This paper serves as a problem statement of the issues surrounding uncertainty in wastewater treatment modelling. The paper proposes a structure for identifying the sources of uncertainty introduced during each step of an engineering project concerned with model-based design or optimisation of a wastewater treatment system. It briefly references the methods currently used to evaluate prediction accuracy and uncertainty and discusses the relevance of uncertainty evaluations in model applications. The paper aims to raise awareness and initiate a comprehensive discussion among professionals on mo

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4

Thomas, R. H., C. L. Hammond, O. G. Bodger, M. I. Rees, and P. E. M. Smith. "Identifying and prioritising epilepsy treatment uncertainties." Journal of Neurology, Neurosurgery & Psychiatry 81, no. 8 (2010): 918–21. http://dx.doi.org/10.1136/jnnp.2009.192716.

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5

SHERMAN, CARL. "New Bipolar Guidelines Reflect Treatment Uncertainties." Internal Medicine News 38, no. 15 (2005): 40. http://dx.doi.org/10.1016/s1097-8690(05)71271-3.

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6

Weise, Klaus. "Treatment of uncertainties in precision measurements." IEEE Transactions on Instrumentation and Measurement IM-36, no. 2 (1987): 642–45. http://dx.doi.org/10.1109/tim.1987.6312760.

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7

Schwarte, J., and H. L. Hein. "Treatment of uncertainties in green engineering." IOP Conference Series: Materials Science and Engineering 615 (October 15, 2019): 012109. http://dx.doi.org/10.1088/1757-899x/615/1/012109.

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8

Kafka, P., and H. Polke. "Treatment of uncertainties in reliability models." Nuclear Engineering and Design 93, no. 2-3 (1986): 203–14. http://dx.doi.org/10.1016/0029-5493(86)90220-7.

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9

de Wert, Guido, and Els Olsthoorn-Heim. "Ovarian Tissue Cryopreservation: Promises and Uncertainties." European Journal of Health Law 16, no. 2 (2009): 173–83. http://dx.doi.org/10.1163/157180909x437132.

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AbstractCancer in children and young adults is increasingly being cured by operations, radiotherapy and/or chemotherapy. However, one of the serious side effects of these treatments is the risk of damage to fertility. Whereas the most important goal used to be survival, now increasing attention is being paid to the quality of life in the long term, thanks to the success of these treatments. Infertility affects the quality of life. In post-pubescent boys and men semen can be frozen for later use prior to treatment that harms the spermatogenesis. In girls and young women the solution for reduced

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10

Dhont, J. "SP-0649 Uncertainties in single fraction treatment." Radiotherapy and Oncology 133 (April 2019): S344. http://dx.doi.org/10.1016/s0167-8140(19)31069-2.

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11

Anderson, R. A., and W. H. Wallace. "Uncertainties in preserving fertility in cancer treatment." BMJ 337, no. 19 1 (2008): a2577. http://dx.doi.org/10.1136/bmj.a2577.

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12

Grilli di Cortona, G., A. Messina, and S. Piacentini. "Treatment of systematic uncertainties with Bayesian networks." Journal of Physics: Conference Series 2438, no. 1 (2023): 012131. http://dx.doi.org/10.1088/1742-6596/2438/1/012131.

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Abstract We show an innovative approach based on Bayesian networks and linear algebra providing a solid and complete solution to the problem of the detector response and the related systematic effects. As a case study, we consider the dark matter direct detection searches. In this context, it is crucial to develop a reliable analysis framework, which is able to take into account all the relevant systematic effects in a clean and accessible way. The relations connecting the calibration parameters of the experiment to the final observed data spectrum are characterized by substantial complexity a

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13

Shimoni, Zvi, and Paul Froom. "Uncertainties in diagnosis, treatment and prevention of trichinellosis." Expert Review of Anti-infective Therapy 13, no. 10 (2015): 1279–88. http://dx.doi.org/10.1586/14787210.2015.1075394.

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14

Booth, Jeremy T. "Modeling the impact of treatment uncertainties in radiotherapy." Medical Physics 29, no. 10 (2002): 2456. http://dx.doi.org/10.1118/1.1510514.

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15

Alber, M. "QUANTIFYING THE ROBUSTNESS OF A TREATMENT AGAINST UNCERTAINTIES." Radiotherapy and Oncology 92 (August 2009): S31. http://dx.doi.org/10.1016/s0167-8140(12)72667-1.

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16

Schwarz, M. "SP-0199: Geometrical uncertainties and proton treatment planning." Radiotherapy and Oncology 111 (2014): S79. http://dx.doi.org/10.1016/s0167-8140(15)30304-2.

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17

Valdagni, R. "SP-0009: Reducing the uncertainties of treatment delivery." Radiotherapy and Oncology 106 (March 2013): S4. http://dx.doi.org/10.1016/s0167-8140(15)32315-x.

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18

van Herk, Marcel, Peter Remeijer, and Joos V. Lebesque. "Inclusion of geometric uncertainties in treatment plan evaluation." International Journal of Radiation Oncology*Biology*Physics 52, no. 5 (2002): 1407–22. http://dx.doi.org/10.1016/s0360-3016(01)02805-x.

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19

Paté-Cornell, M. Elisabeth. "Uncertainties in risk analysis: Six levels of treatment." Reliability Engineering & System Safety 54, no. 2-3 (1996): 95–111. http://dx.doi.org/10.1016/s0951-8320(96)00067-1.

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20

Kutcher, G. J., G. S. Mageras, C. Chui, et al. "Inclusion of systematic setup uncertainties in treatment plans." International Journal of Radiation Oncology*Biology*Physics 30 (January 1994): 241–42. http://dx.doi.org/10.1016/0360-3016(94)90778-1.

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21

Dalzell, J. R., and J. A. Cannon. "Uncertainties about medical treatment of acute heart failure." BMJ 349, no. 12 3 (2014): g6702. http://dx.doi.org/10.1136/bmj.g6702.

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22

Rapport, Frances L., Gabi S. Jerzembek, Marcus A. Doel, Aled Jones, Matteo Cella, and Keith R. Lloyd. "Narrating uncertainties about treatment of mental health conditions." Social Psychiatry and Psychiatric Epidemiology 45, no. 3 (2009): 371–79. http://dx.doi.org/10.1007/s00127-009-0072-y.

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23

Xu, Huijun, J. James Gordon, and Jeffrey V. Siebers. "Coverage-based treatment planning to accommodate delineation uncertainties in prostate cancer treatment." Medical Physics 42, no. 9 (2015): 5435–43. http://dx.doi.org/10.1118/1.4928490.

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24

Coelho, Flávio Codeço, Cláudia Torres Codeço, and Claudio José Struchiner. "Complete treatment of uncertainties in a model for dengue R0 estimation." Cadernos de Saúde Pública 24, no. 4 (2008): 853–61. http://dx.doi.org/10.1590/s0102-311x2008000400016.

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In real epidemic processes, the basic reproduction number R0 is the combined outcome of multiple probabilistic events. Nevertheless, it is frequently modeled as a deterministic function of epidemiological variables. This paper discusses the importance of adequate treatment of uncertainties in such models. This is done by comparing two methods of uncertainty analysis: Monte Carlo uncertainty analysis (MCUA) and the Bayesian melding (BM) method. These methods are applied to a model for the determination of R0 of dengue fever based on entomological parameters. The BM was shown to provide a comple

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25

Schulz, Volker, and Claudia Schillings. "Problem Formulations and Treatment of Uncertainties in Aerodynamic Design." AIAA Journal 47, no. 3 (2009): 646–54. http://dx.doi.org/10.2514/1.37955.

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26

Li, J. S., M. H. Lin, L. Wang, and C.-M. Ma. "SU-E-T-431: Dosimetric Uncertainties in RapidArc Treatment." Medical Physics 38, no. 6Part17 (2011): 3587. http://dx.doi.org/10.1118/1.3612385.

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27

Ma, C.-M., J. S. Li, S. B. Jiang, et al. "Effect of statistical uncertainties on Monte Carlo treatment planning." Physics in Medicine and Biology 50, no. 5 (2005): 891–907. http://dx.doi.org/10.1088/0031-9155/50/5/013.

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28

Deasy, Joseph O., K. S. Clifford Chao, and Jerry Markman. "Uncertainties in model-based outcome predictions for treatment planning." International Journal of Radiation Oncology*Biology*Physics 51, no. 5 (2001): 1389–99. http://dx.doi.org/10.1016/s0360-3016(01)02659-1.

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29

Lee, Yang Gul, and Michael F. Malone. "A General Treatment of Uncertainties in Batch Process Planning." Industrial & Engineering Chemistry Research 40, no. 6 (2001): 1507–15. http://dx.doi.org/10.1021/ie9907122.

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30

Harron, Elizabeth Christine, Hazel Mhairi McCallum, Elizabeth Lyn Lambert, Daniela Lee, and Geoffrey David Lambert. "Dosimetric Effects of Setup Uncertainties on Breast Treatment Delivery." Medical Dosimetry 33, no. 4 (2008): 293–98. http://dx.doi.org/10.1016/j.meddos.2008.01.003.

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31

Kutcher, G. J. "246Treatment uncertainties: Some strategies for treatment design and delivery." Radiotherapy and Oncology 40 (January 1996): S65. http://dx.doi.org/10.1016/s0167-8140(96)80255-6.

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32

Sun, Werner M. "Simultaneous least-squares treatment of statistical and systematic uncertainties." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 556, no. 1 (2006): 325–30. http://dx.doi.org/10.1016/j.nima.2005.10.030.

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33

Reynaert, N. "PET and MRI based RT treatment planning: Handling uncertainties." Cancer/Radiothérapie 23, no. 6-7 (2019): 753–60. http://dx.doi.org/10.1016/j.canrad.2019.08.002.

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34

Kutcher, G. J., C. Chui, and T. LoSasso. "Incorporation of set-up uncertainties in treatment planning calculations." International Journal of Radiation Oncology*Biology*Physics 21 (January 1991): 123–24. http://dx.doi.org/10.1016/0360-3016(91)90449-e.

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35

Lomax, A. J. "Intensity modulated proton therapy and its sensitivity to treatment uncertainties 1: the potential effects of calculational uncertainties." Physics in Medicine and Biology 53, no. 4 (2008): 1027–42. http://dx.doi.org/10.1088/0031-9155/53/4/014.

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36

Guo, Fengdi, Jeremy Gregory, and Randolph Kirchain. "Probabilistic Life-Cycle Cost Analysis of Pavements Based on Simulation Optimization." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 5 (2019): 389–96. http://dx.doi.org/10.1177/0361198119838984.

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Life-cycle cost analysis (LCCA) is a way to evaluate the long-term cost effectiveness of different pavement designs or treatment actions. Owing to the existence of uncertainties, many probabilistic LCCA models have been proposed. They mainly use a prescribed treatment schedule or determine schedules by mechanistic-empirical analysis, potentially leading to the overestimation of life-cycle cost (LCC). In this paper, a new probabilistic simulation-optimization LCCA model is proposed. This new model determines treatment schedules by minimizing total LCC, including agency and user cost, which is d

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37

Blake, Samuel J., Sankar Arumugam, Lois Holloway, et al. "Investigating the impact of treatment delivery uncertainties on treatment effectiveness for lung SABR." Australasian Physical & Engineering Sciences in Medicine 40, no. 4 (2017): 823–29. http://dx.doi.org/10.1007/s13246-017-0591-x.

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38

Gaarder, Jørn Emil, Hans Olav Hygen, Rolf André Bohne, and Tore Kvande. "Building Adaptation Measures Using Future Climate Scenarios—A Scoping Review of Uncertainty Treatment and Communication." Buildings 13, no. 6 (2023): 1460. http://dx.doi.org/10.3390/buildings13061460.

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The global climate is changing. Predicting the impacts this will have on buildings is the first step in the process of finding suitable building adaptation measures. Future climate adaptation of buildings and infrastructure is a growing field of research, relying on both socio-economical and meteorological research for input values to the simulation models. Models producing hourly future weather data rely on global climate models which are based on emission scenarios made from assumptions of future political, social, and economic developments. Accounting for the uncertainties from these underl

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39

Eisenthal, Sherman, Cheryl Koopman, and John D. Stoeckle. "Relationship of Patients' Pain Reports to Their Requests in Two Medical Settings." Psychological Reports 62, no. 3 (1988): 719–26. http://dx.doi.org/10.2466/pr0.1988.62.3.719.

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Do patients' uncertainties about what their pain sensations mean influence their reports of pain? To study this question, patients' pain reports were examined within two hospital-based medical practices, a walk-in unit and a general medical practice, practices to which patients bring different uncertainties about their diagnosis and treatment. Patients' requests for medical help are a measure of such uncertainties. Within each practice requests of patients reporting pain were compared with those of nonreporters. In the walk-in unit, where new patients face diagnostic uncertainties, pain report

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40

Ibrahim, R. A. "Structural Dynamics with Parameter Uncertainties." Applied Mechanics Reviews 40, no. 3 (1987): 309–28. http://dx.doi.org/10.1115/1.3149532.

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The treatment of structural parameters as random variables has been the subject of structural dynamicists and designers for many years. Several problems have been involved during the last few decades and resulted in new theorems and interesting phenomena. This paper reviews a number of topics pertaining to structural dynamics with parameter uncertainties. These include direct problems such as random eigenvalues and random responses of discrete and continuous systems. The impact of these problems on related areas of interest such as sensitivity of structural performance to parameter variations,

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41

Rogers, Leland, Igor Barani, Marc Chamberlain, et al. "Meningiomas: knowledge base, treatment outcomes, and uncertainties. A RANO review." Journal of Neurosurgery 122, no. 1 (2015): 4–23. http://dx.doi.org/10.3171/2014.7.jns131644.

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Evolving interest in meningioma, the most common primary brain tumor, has refined contemporary management of these tumors. Problematic, however, is the paucity of prospective clinical trials that provide an evidence-based algorithm for managing meningioma. This review summarizes the published literature regarding the treatment of newly diagnosed and recurrent meningioma, with an emphasis on outcomes stratified by WHO tumor grade. Specifically, this review focuses on patient outcomes following treatment (either adjuvant or at recurrence) with surgery or radiation therapy inclusive of radiosurge

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42

Grabois, Martin, and Andrew SC Rice. "Navigating the uncertainties of pain management to provide optimal treatment." Pain Management 1, no. 1 (2011): 1–2. http://dx.doi.org/10.2217/pmt.10.12.

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43

Filho, João Inácio Da Silva. "Treatment of Uncertainties with Algorithms of the Paraconsistent Annotated Logic." Journal of Intelligent Learning Systems and Applications 04, no. 02 (2012): 144–53. http://dx.doi.org/10.4236/jilsa.2012.42014.

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44

Kletting, Marco, Andreas Rauh, Harald Aschemann, and Eberhard P. Hofer. "CONSISTENCY TECHNIQUES FOR SIMULATION OF WASTEWATER TREATMENT PROCESSES WITH UNCERTAINTIES." IFAC Proceedings Volumes 38, no. 1 (2005): 171–76. http://dx.doi.org/10.3182/20050703-6-cz-1902.02232.

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45

Heath, Emily, Jan Unkelbach, and Uwe Oelfke. "Incorporating uncertainties in respiratory motion into 4D treatment plan optimization." Medical Physics 36, no. 7 (2009): 3059–71. http://dx.doi.org/10.1118/1.3148582.

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46

Ghofrani, Hossein A., Martin W. Wilkins, and Stuart Rich. "Uncertainties in the Diagnosis and Treatment of Pulmonary Arterial Hypertension." Circulation 118, no. 11 (2008): 1195–201. http://dx.doi.org/10.1161/circulationaha.106.674002.

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47

Spencer, F. A., A. Iorio, J. You, et al. "Uncertainties in baseline risk estimates and confidence in treatment effects." BMJ 345, no. 14 1 (2012): e7401-e7401. http://dx.doi.org/10.1136/bmj.e7401.

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48

Mageras, G. S., E. Melian, Z. Fuks, S. M. Leibel, R. Mohan, and G. J. Kutcher. "Incorporation of organ motion uncertainties into 3d prostate treatment plans." International Journal of Radiation Oncology*Biology*Physics 30 (January 1994): 175–76. http://dx.doi.org/10.1016/0360-3016(94)90665-3.

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49

Stathakis, S., C. Shi, P. Mavroidis, et al. "Use of Megavoltage CT Imaging for Quantifying Treatment Setup Uncertainties." International Journal of Radiation Oncology*Biology*Physics 72, no. 1 (2008): S660. http://dx.doi.org/10.1016/j.ijrobp.2008.06.348.

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50

Tegenfeldt, Fredrik, and Jan Conrad. "On Bayesian treatment of systematic uncertainties in confidence interval calculation." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 539, no. 1-2 (2005): 407–13. http://dx.doi.org/10.1016/j.nima.2004.09.037.

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