In this work we propose a method based on the Bee Colony Optimization (BCO) to find an optimal flight gate assignment for a given schedule
A logical approach to gate layout • All complementary gates may be designed using a single row of n-transistors above or below a single row of p-
GATE: Graphic Appraisal Tool for Epidemiology Graphic Architectural Tool for Epidemiology Graphic Approach To Epidemiology making epidemiology accessible
The GATE frame: • Graphic Appraisal Tool for Epidemiological studies – a framework for appraising studies • Graphic Architectural Tool for Epidemiological
The robust approach is to make sure that the airport gate assignment is feasible for all possible value for the real-time arrival and departure
This study propounds a hybrid fuzzy- multi criteria decision making (MCDM) approach where fuzzy-analytical hierarchy process (AHP) is used to determine the
IEEE TRANSACTIONS ON ELECTRON DEVICES, VOL 53, NO 2, FEBRUARY 2006 Recessed-Gate Structure Approach Toward Normally Off High-Voltage AlGaN/GaN HEMT for
Abstract We present in this paper an application of the Constructive Genetic Algorithm (CGA) to the Linear Gate Assignment Problem (LGAP) The LGAP
Carlo method The Airport gate assignment problem (AGAP) seeks to find feasible flight to gate assignments so that the number of the flights that need be
GATE: Graphic Appraisal Tool for Epidemiology Graphic Approach To Epidemiology every epidemiological study can be hung on the GATE frame
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GATE: Graphic Appraisal Tool for Epidemiology
1991 - 2015
1 1 picture, 2 formulas & 3 acronyms
GATE: Graphic Appraisal Tool for Epidemiology Graphic Architectural Tool for Epidemiology Graphic Approach To Epidemiology making epidemiology accessible
2 presentation outline
GATE is a framework for:
1.study design
2.study analysis
3.study error
4.practicing EBM
3 1 picture, 2 formulas & 3 acronyms
GATE: a framework for study design
1 picture 5 every epidemiological study can be hung on the GATE frame
1 picture, 2 formulas & 3 acronyms
cohort of British doctors non-smokers smokers lung cancer events counted yes no followed for 10 years smoking status allocated by measurement (observation) cohort / longitudinal / follow-up study 6
1 picture: GATE frame
1 picture, 2 formulas & 3 acronyms
British doctors
placebo aspirin MI yes no 5 years randomly allocated to aspirin or placebo 7
1st acronym: PECOT
Participants
Comparison Exposure
Outcomes
Time P E C O T randomised controlled trial
1 picture, 2 formulas & 3 acronyms
middle-aged Americans
͚normal͛ weight overweight
diabetes status measured in all participants yes no body mass index measured cross-sectional (prevalence) study 8 P E C O T middle-aged American women breast cancer mammogram negative yes no receive mammogram screening test diagnostic test (prediction) study mammogram positive 9 P E C O T middle-aged American women mammogram test no breast cancer positive negative
Gold Standard
diagnostic (test accuracy) study breast cancer 10 P E C O T non-smokers smokers lung cancer yes no smoking status measured case-control study 11 P E C O T cases controls (all nested in virtual cohort studies) $10,000
GATE: a framework for study analysis:
1st formula: occurrence = outcomes р population 14 the numbers in epidemiological studies can be hung on the
GATE frame
1 picture, 2 formulas & 3 acronyms
British doctors
non-smokers smokers
Lung cancer
yes no 10 years smoking status measured 15
1st formula: occurrence of outcomes =
number of outcomes р number in population/group
Participant Population
Comparison Group Exposure Group
Outcomes Time
P
EG CG
O T a b
British doctors
non-smokers smokers
Lung cancer
yes no 10 years smoking status measured 16
Population
Comparison Group Exposure Group
Outcomes Time
P
EG CG
O T
Exposure Group Occurrence (EGO) = aрEG
= number of outcomes (a) р number in exposed population (EG) a b
British doctors
placebo aspirin MI yes no 5 years randomly allocated 17
Population
Comparison Group Exposure Group
Outcomes Time
P
EG CG
O T a b
Comparison Group Occurrence (CGO) = bрCG
= number of outcomes (b) р number in comparison population (CG) yes no 18
Epidemiology = Numerator р Denominator
Participant Population
Comparison Group Exposure Group
Outcomes Time
P EG D O
T a N
middle-aged American women breast cancer mammogram negative receive mammogram screening test mammogram positive
British doctors
non-smokers smokers
Lung cancer
yes no
10 years
smoking status measured 19 the goal of all epidemiological studies is to calculate EGO and CGO P
EG CG
O T a b EGO:
Occurrence (risk) of
cancer in smokers CGO:
Occurrence of
cancer in non- smokers
Middle-aged Americans
Low BMI High BMI
EGO:
Average blood
glucose in EG high low
Body Mass Index (BMI) measured
20 P
EG CG
O CGO:
Average blood
glucose in CG
Middle-aged American women
mammogram no Breast cancer positive negative
Gold Standard
Breast cancer
21
P E C O T EGO: likelihood of a positive mammogram if breast cancer CGO: likelihood of a positive mammogram if no breast cancer
EGO ÷ CGO = Relative Risk (RR)
EGO - CGO = Risk Difference (RD)
its all about EGO and CGO measures of occurrence: risk; rate; likelihood; probability; average; incidence; prevalence 22
1st formula:
occurrence = outcomes р population
GATE: framework for nonrandom error
2nd acronym: RAMBOMAN
24
Recruitment
Allocation
Maintenance
Blind
Objective
Measurements
ANalyses
1 picture, 2 formulas & 3 acronyms
RAMBOMAN
Recruitment of participants
͚who are the findings applicable to͍͛
P P
Study setting
Eligible population
25
recruitment process
EG CG
O T
RCT: allocated by randomisation
(e.g to drugs)
EG CG
O T
Cohort: allocated by
measurement (e.g. smoking) RAMBOMAN: ͚were participants well Allocated to edžposure Θ comparison groups͍͛
EG & CG
similar at baseline? was Allocation to EG & CG successful? 26
E & C
measures accurate?
RAMBOMAN
EG CG
O T
͚were Participants well Maintained in
the groups they were allocated to͍͛ P completeness of follow-up compliance contamination co-interventions 27
RAMBOMAN
EG CG
O T
͚were outcomes well Measured͍͛
were they measured Blind to whether participant was in EG or CG ? P 28
RAMBOMAN
EG CG
O T
͚were outcomes well Measured͍͛
were they measured Objectively? P 29
RAMBOMAN
EGC CGC
O T P 30
EGA CGA
a b
͚were the ANalyses done well͍͛
If RCT were Intention To Treat (ITT)
analyses done?
RAMBOMAN
EG CG
O T
͚were the ANalyses done well͍͛
P adjustment for baseline differences / confounding? 31
GATE: random error: 2nd formula:
random error = 95% confidence interval 32
There is about a 95% chance that the true value in the underlying population lies within the 95% CI (assuming no non-random error)
EGO ц 95% CI CGO ц 95% CI
1 picture, 2 formulas & 3 acronyms
GATE: a framework for error in
systematic reviews & meta-analyses:
3rd acronym: FAITH
1 picture, 2 formulas & 3 acronyms
33
study sources studies appraised & allocated: included excluded studies summarised & pooled if homogeneous systematic review: a study of studies studies screened 34
study sources studies appraised & allocated: included excluded studies summarised & pooled if homogeneous studies screened critical appraisal of SR: FAITH Find
Appraise
Include
Total
Heterogeneity?
1 picture, 2 formulas & 3 acronyms
35
GATE: framework for the 4 steps of
Evidence Based Practice (EBP)
37
the steps of EBP:
1.Ask
2.Access
3. Appraise
4. Apply & Act
38
yes no 39
1. Participants
3. Comparison 2. Exposure
4. Outcomes
5. Time
P E C O T
EBP Step 1: ASK - turn your question
into a focused 5-part PECOT question
EBP Step 2: ACCESS the evidence - use
PECOT to help choose search terms
40
yes no
Participants
Comparison Exposure
Outcomes
Time P E C O T P E C O T P E C O T
Recruitment
Allocation
Maintenance
blind objective
Measurements
ANalyses
41
EBP Step 3: APPRAISE the evidence -
with the picture, acronyms & formulas
Occurrence = outcomes ÷ population
Random error = 95% Confidence Interval
APPLY the evidence by AMALGAMATING the
relevant information & making an evidence- based decision͗͛ the X-factor
© 42
43
epidemiological evidence patient͛s clinical circumstances system features values & preferences
X-factor: making evidence-based decisions
Practitioner eXpertise͗ ͚putting it all together͛ - the art of practice economic legal political person family community practitioner
Clinical expertise in the era of evidence-based medicine and patient choice. EBM 2002;736-8 (March/April) 44
GATE critically appraised topic
(CATs) forms
GATE CAT - 3-sheet workbook (in Excel)
sheet 1: GATE-Ask & Access 46
47
GATE CAT - 3-sheet workbook (in Excel)
sheet 2: GATE-Appraise (with calculator) 48
GATE CAT - 3-sheet workbook (in Excel)
sheet 3: GATE-Apply