BME100 f2014:Group28 L6: Difference between revisions

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'''Overview of the Original Diagnosis System'''
'''Overview of the Original Diagnosis System'''
<!-- Instructions: Write a medium-length summary (~10 - 20 sentences) of how BME100 tested patients for the disease-associated SNP. Describe (A) the division of labor (e.g., 34 teams of 6 students each diagnosed 68 patients total...), (B) things that were done to prevent error, such as the number of replicates per patient, PCR controls, ImageJ calibration controls, and the number of drop images that were used for the ImageJ calculations (per unique PCR sample), and (C) the class's final data from the BME100_fa2014_PCRResults spreadsheet (successful conclusions, inconclusive results, blank data). -->
<!-- Instructions: Write a medium-length summary (~10 - 20 sentences) of how BME100 tested patients for the disease-associated SNP. Describe (A) the division of labor (e.g., 34 teams of 6 students each diagnosed 68 patients total...), (B) things that were done to prevent error, such as the number of replicates per patient, PCR controls, ImageJ calibration controls, and the number of drop images that were used for the ImageJ calculations (per unique PCR sample), and (C) the class's final data from the BME100_fa2014_PCRResults spreadsheet (successful conclusions, inconclusive results, blank data). -->
 
A) The labor for this lab was split up between 34 teams diagnosing 68 patients.  This means that 2 patients were given to each group.  Each team had 6 students in them. 
B) 


'''What Bayes Statistics Imply about This Diagnostic Approach'''
'''What Bayes Statistics Imply about This Diagnostic Approach'''

Revision as of 15:20, 19 November 2014

BME 100 Fall 2014 Home
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Lab Write-Up 1 | Lab Write-Up 2 | Lab Write-Up 3
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OUR COMPANY

Name: Andrew W. Hamidy
Name: Kyle Brague
Name: Brandt Hansen
Name: student
Name: student
Name: student

phlapps

LAB 6 WRITE-UP

Bayesian Statistics

Overview of the Original Diagnosis System A) The labor for this lab was split up between 34 teams diagnosing 68 patients. This means that 2 patients were given to each group. Each team had 6 students in them. B)

What Bayes Statistics Imply about This Diagnostic Approach


Computer-Aided Design

TinkerCAD


Our Design


Our Design includes vents that automatically open and close based on the temperature inside the PCR machine. This will improve energy and cost efficiency since less energy will be lost to the surroundings. The vents are automatically controlled by servos that take information from a temperature inside the machine. We chose this design because we realized how ignored vents are in contemporary electronics.


Feature 1: Consumables Kit

Feature 2: Hardware - PCR Machine & Fluorimeter