BME103 s2013:T900 Group4 L3
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(→New System: Design Strategy) 
(→Original System: PCR Results) 

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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 =  +  * A = frequency of cancerpositive conclusions = 9 / 20 = 0.45 
  * B = frequency of positive PCR reactions =  +  * B = frequency of positive PCR reactions = 26 / 60 = 0.43 
  * P (BA) = frequency of positive PCR given cancerpositive conclusion =  +  * P (BA) = frequency of positive PCR given cancerpositive conclusion = 24 / 26 = 0.92 
  * '''P(AB) =  +  * '''P(AB) = 0.96 = 96%''' 
<br>  <br>  
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 =  +  * A = frequency of cancernegative conclusions = 11 / 20 = 0.55 
  * B = frequency of negative PCR reactions =  +  * B = frequency of negative PCR reactions = 34 / 60 = 0.57 
  * P (BA) = frequency of negative PCR given cancernegative conclusion =  +  * P (BA) = frequency of negative PCR given cancernegative conclusion = 31 / 34 = 0.91 
  * '''P(AB) =  +  * '''P(AB) = 0.88 = 88%''' 
<br>  <br>  
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 =  +  * A = frequency of "yes" cancer diagnosis = 9 / 20 = 0.45 
  * B = frequency of "pos" test conclusion =  +  * B = frequency of "pos" test conclusion = 26 / 60 = 0.43 
  * P (BA) = frequency of pos given yes =  +  * P (BA) = frequency of pos given yes = 24 / 26 = 0.92 
  * '''P(AB) =  +  * '''P(AB) = 0.96 = 96%''' 
<br>  <br>  
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 =  +  * A = frequency of "no" cancer diagnosis = 11 / 20 = 0.55 
  * B = frequency of "neg" test conclusion =  +  * B = frequency of "neg" test conclusion = 34 / 60 = 0.57 
  * P (BA) = frequency of neg given no =  +  * P (BA) = frequency of neg given no = 31 / 34 = 0.91 
  * '''P(AB) =  +  * '''P(AB) = 0.88 = 88%''' 
<br>  <br>  
Revision as of 05:07, 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  
OUR TEAMLAB 3 WRITEUPOriginal System: PCR ResultsPCR Test Results
* Ave. INTDEN = Average of ImageJ integrated density values from three Fluorimeter images
Calculation 3: The probability that the patient will develop cancer, given a cancer 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
KEY FEATURES
Step 1: Connect the base to the fluorimeter.
New System: ProtocolsDESIGN
MATERIALS
New System: Research and DevelopmentBACKGROUND
DESIGN
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New System: Software[THIS SECTION IS OPTIONAL. If your team has creative ideas for new software, and new software is a key component included in your new protocols, R&D, or machine design, you may describe it here. You will not receive bonus points, but a solid effort may raise your overall page layout points. If you decide not to propose new software, please delete this entire section, including the ==New System: Software== header.]
