'Survival curve' diaporamas de présentation

Population Dynamics

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Dynamics of HIV

Dynamics of HIV. By Bio 475 Seminar Class Fall 1998. Introduction. HIV (Human Immunodeficiency Virus) is the causative factor of the disease known as AIDS (Acquired Immune Deficiency Syndrome) According to the CDC (Center for Disease Control) 1993 definition a person has AIDS when:

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Objectives

The Radiobiology Behind Dose Fractionation Bill McBride Dept. Radiation Oncology David Geffen School Medicine UCLA, Los Angeles, Ca. wmcbride@mednet.ucla.edu. Objectives. To understand the mathematical bases behind survival curves Know the linear quadratic model formulation

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OUTCOME EVALUATION AND COST-EFFECTIVENESS IN HEALTHCARE INDUSTRY

OUTCOME EVALUATION AND COST-EFFECTIVENESS IN HEALTHCARE INDUSTRY. Jung-Der Wang, M.D., Sc. D. National Taiwan University College of Public Health National Taiwan University Hospital. OUTLINES.

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Biostat 209 Survival Data l

Biostat 209 Survival Data l. John Kornak April 2, 2013 John.kornak@ucsf.edu Reading VGSM 3.5 (review) and 6.1 - 6.2.4 http://www. epibiostat.ucsf.edu/biostat/vgsm/. Logistics. Lectures in 6702 every Tuesday ***EXCEPT*** additional lecture Thursday 4/19

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STATISTICS 542 Intro to Clinical Trials SURVIVAL ANALYSIS

STATISTICS 542 Intro to Clinical Trials SURVIVAL ANALYSIS. Survival Analysis Terminology. Concerned about time to some event Event is often death Event may also be, for example 1. Cause specific death 2. Non-fatal event or death, whichever comes first death or hospitalization

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STATISTICS 542 Intro to Clinical Trials SURVIVAL ANALYSIS

STATISTICS 542 Intro to Clinical Trials SURVIVAL ANALYSIS. Survival Analysis Terminology. Concerned about time to some event Event is often death Event may also be, for example 1. Cause specific death 2. Non-fatal event or death, whichever comes first death or hospitalization

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?????????? ???? ??? http://genomed.dlearn.kmu.edu.tw. Survival curve = radiation dose & cell survival fraction. Reproductive Integrity. Cell survival ?? cell death. For differentiated cells that do not proliferate e.g., nerve, muscle ? lose of specific function (death).

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Current and future roles of public and private health care in Canada

Current and future roles of public and private health care in Canada. Chris Smith Sabina Nagpal (Meds class of 2007). Overview of this session. The current state of Canadian health care funding Historical forces pushing for and against change in Canadian health care

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Empirical Analysis of a Telephone Call Center

Empirical Analysis of a Telephone Call Center. Anat Sakov Joint work with Avishai Mandelbaum, Sergey Zeltyn, Larry Brown, Linda Zhao and Heipeng Shen Statistics Seminar, Tel Aviv University, 29.5.01. Introduction.

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Chapter 11 Survival Analysis Part 1

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Survival Analysis

Survival Analysis. Key variable = time until some event. time from treatment to death time for a fracture to heal time from surgery to relapse. Censored observations. subjects removed from data set at some stage without suffering an event

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Screening for Alzheimer's Disease Relation to Risk, Benefit Age and Genotype

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Modifiers of Cell Survival: Oxygen Effect

LECTURE 9. Modifiers of Cell Survival: Oxygen Effect. Modifiers of Cell Survival: Oxygen Effect. Definition of OER. Effects of dose, dose rate, cell type. OER as a function of LET. Impact of O 2 concentration. Time scale of oxygen effect.

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Survival analysis

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BMS 617

BMS 617. Lecture 10: Survival Curves. Survival Data. The term survival data refers to the measurement of the time it takes for an event to happen The event does not have to be death (so the measurement is the amount of time the subject survived)

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When Using DOPPS Slides

When Using DOPPS Slides. DOPPS Slide Use Guidelines. Correlates and Outcomes of Dementia among Dialysis Patients: the Dialysis Outcomes and Practice Patterns Study . Introduction . DOPPS Background . Methods (1). Methods (2).

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Kaplan-Meier Estimator

Statistics2013 Poster. Kaplan-Meier Estimator. Bo Huang, Ching-Ray Yu and Christy Chuang-Stein Pfizer Inc. Statistics Saves Lives. The History of the Kaplan-Meier Estimator.

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Epidemic Curves Sensitivity/Specificity

Epidemic Curves Sensitivity/Specificity. Epidemic Curve. Number of New Cases. Time (since exposure). Notes on Epidemic Curves. Sort by time to illness Think critically about the data (possible problems) Ask questions (or make assumptions) Similar to Survival Curve (see text, p492).

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Anna Fabisiewicz 1 , Andrzej Tysarowski 1 ,Michal Osowiecki 2 ,

Progression- free survival curve in whole group of patients. 1,0. 0,8. 0,6. Probability of PFS. 0,4. 0,2. V. 0,0. V/F. 0. 20. 40. 60. 80. 100. 120. 140. 160. 180. 200. Months. 0. 10. 20. 30. 40. 50. 60. 70. Months.

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