Difference between revisions of "BME103 s2013:T900 Group4 L3"
Anna Essex (talk  contribs) (→Original System: PCR Results) 
Anna Essex (talk  contribs) (→Original System: PCR Results) 

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Bayes Theorem equation: P(AB) = P(BA) * P(A) / P(B)  Bayes Theorem equation: P(AB) = P(BA) * P(A) / P(B)  
−  +  '''Calculation 1:''' The probability that the sample actually has the cancer DNA sequence, given a positive diagnostic signal.<br>  
−  Calculation 1: The probability that the sample actually has the cancer DNA sequence, given a positive diagnostic signal.<br>  
* A = frequency of cancerpositive conclusions = 9 / 20 = 0.45  * A = frequency of cancerpositive conclusions = 9 / 20 = 0.45  
* B = frequency of positive PCR reactions = 26 / 60 = 0.43  * B = frequency of positive PCR reactions = 26 / 60 = 0.43  
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−  +  '''Calculation 2:''' The probability that the sample actually has a noncancer DNA sequence, given a negative diagnostic signal.<br>  
−  Calculation 2: The probability that the sample actually has a noncancer DNA sequence, given a negative diagnostic signal.<br>  
* A = frequency of cancernegative conclusions = 11 / 20 = 0.55  * A = frequency of cancernegative conclusions = 11 / 20 = 0.55  
* B = frequency of negative PCR reactions = 34 / 60 = 0.57  * B = frequency of negative PCR reactions = 34 / 60 = 0.57  
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−  Calculation 3: The probability that the patient will develop cancer, given a cancer DNA sequence.<br>  +  '''Calculation 3:''' The probability that the patient will develop cancer, given a cancer DNA sequence.<br> 
* A = frequency of "yes" cancer diagnosis = 9 / 20 = 0.45  * A = frequency of "yes" cancer diagnosis = 9 / 20 = 0.45  
* B = frequency of "pos" test conclusion = 26 / 60 = 0.43  * B = frequency of "pos" test conclusion = 26 / 60 = 0.43  
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−  +  '''Calculation 4:''' The probability that the patient will not develop cancer, given a noncancer DNA sequence.<br>  
−  Calculation 4: The probability that the patient will not develop cancer, given a noncancer DNA sequence.<br>  
* A = frequency of "no" cancer diagnosis = 11 / 20 = 0.55  * A = frequency of "no" cancer diagnosis = 11 / 20 = 0.55  
* B = frequency of "neg" test conclusion = 34 / 60 = 0.57  * B = frequency of "neg" test conclusion = 34 / 60 = 0.57 
Revision as of 04:08, 16 April 2013
BME 103 Spring 2013  Home People Lab WriteUp 1 Lab WriteUp 2 Lab WriteUp 3 Course Logistics For Instructors Photos Wiki Editing Help  
ContentsOUR TEAMLAB 3 WRITEUPOriginal System: PCR ResultsPCR Test Results
* Ave. INTDEN = Average of ImageJ integrated density values from three Fluorimeter images
Calculation 1: The probability that the sample actually has the cancer DNA sequence, given a positive diagnostic signal.
Calculation 2: The probability that the sample actually has a noncancer DNA sequence, given a negative diagnostic signal.
Calculation 3: The probability that the patient will develop cancer, given a cancer DNA sequence.
Calculation 4: The probability that the patient will not develop cancer, given a noncancer DNA sequence.
New System: Design StrategyWe concluded that a good system Must Have:  easily determined results: The easier the results are to read accurately, the less likely a misdiagnosis in either direction. It is undesirable both to give a false negative, where a patient is not treated when care is needed, or to give a false positive, wasting time and resources on those who do not need them. This aspect is central to any diagnostic tool.  Simple OpenPCR Software: Simplicity increases ease and efficiency in lab experiments and hopefully leads to faster diagnoses. It also makes troubleshooting easier should problems arise. The more straightforward the system, the more quickly users can learn to use the machine. We concluded that we would Want a good system to have:  Low cost: Currently an OpenPCR machine costs $599 and a Fluorimeter costs $300. An inexpensive material would help reduce cost and increase accessibility, since there is always a limited budget for new equipment. This would not only allow users to increase the amount of tests that can be run at the same time, but also boost sales, which is important for marketing any device.  integrated camera: phone cameras are easily moveable and vary in size and quality, leading to differing results. Smartphone camera settings can be time consuming or nonexistent. Having a builtin camera increases cost, but it is worth it to increase speed and accuracy. Furthermore, the program is simpler because it does not have to adjust to different cameras and phone sizes and shapes vary enough to make building a cradle to fit them difficult.
 Troublesome USB Connectivity. USB connectivity should function well in order for OpenPCR machine to work.  Casing = fire hazard. High temperature with PCR can be dangerous.
We concluded that a good system Should Avoid:  Avoid slow amplification.  Hard to adjust phone/ fluorimeter. The phone can be easily moved by accident, which requires readjustment between the phone and the fluorimeter.
New System: Machine/ Device EngineeringSYSTEM DESIGN
Fluorimeter  We chose to include these new features:
PCR Machine  We chose keep these features the same as the original system:
New System: ProtocolsDESIGN
New System: Research and DevelopmentBACKGROUND
DESIGN
GGAAGTGGGTCCTAAAAACTCTTACA[C/T]TGCATACATAGAAGATCACAGTGGC
New System: SoftwareAs has been seen by the several groups who already have software in development, the need for more efficient PCR and image analysis capabilities are growing. For our particular machine, an app allowing a smartphone to control the integrated fluorimeter camera would be most essential, and ideally this app could also perform image analysis, lessening the complication of transferring large quantities of images that all look very similar to the human eye.
