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Doctors Without Borders Foundation: Antibiogo banner
Program
1
Project

Status:
Draft
Launch:
April 28, 2021

Doctors Without Borders Foundation: Antibiogo


By 2050, Antimicrobial resistance is expected to cause 10 million deaths per year, overwhelmingly in low-income countries. Antibiogo, is a free, offline, privacy-focused, and open-source Android app that helps clinicians prescribe the right antibiotics by using computer vision and expert decision trees. The MSF Foundation, together with JOGL, needs your help gathering enough experimental data to train our open-source, clinical image recognition algorithm.

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❗️ESSENTIAL UPDATE: Please declare your intention to participate as soon as possible as we need all pictures/data to be submitted by the end of June.

Join our Slack group to be in direct contact with us by clicking HERE 

If you wish to participate, but have an issue doing so by the deadline above, please contact Paige at paige@jogl.io.

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 📌 On May 5, microbiologist and scientific lead for Antibiogo Nada Malou held an information session and Q&A on this program with our CEO Thomas Landrain. A must watch for likely participants with questions and seeking further details.


Catch the whole event here:


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🚨 JOIN THE FIGHT AGAINST 🚨

🚨 ANTIMICROBIAL RESISTANCE 🚨


JOGL is partnering with La Fondation Médecins Sans Frontières/The Doctors Without Borders Foundation in the continued development of the open-source Antibiogo app, which uses computer vision and expert decision trees to combat antimicrobial resistance.


If action isn't taken today, it is projected that, by 2050, there will be 10 million deaths per year attributed to antimicrobial resistance. That's why The MSF Foundation has developed Antibiogo: to tackle the issue firsthand and to make true their commitment to aiding low-income countries.


By automatically detecting specific Antibiotic Susceptibility Testing (AST) compounds, such as pellet names and inhibition zone diameters, Antibiogo, a free, offline, privacy-focused, and open-source Android app, eases MSF's field laboratory technicians’ measurements.


But Antibiogo can’t function on its own.


The app's machine learning relies on a database of AST results humanly calibrated by the capturing and sharing of result images. The greater the database, the more effectively Antibiogo functions. That's why we need you:


We need your help collecting data.

CALLING ALL MICROBIOLOGISTS!


Are you ready? Help make Antibiogo by The MSF Foundation an even more effective tool for the communities who need it. Use your skills and laboratory access to perform ASTs of specific antibiotics and share your results (pictures). All selected participants will be reimbursed for the lab consumables they use (see reimbursement section of the challenge FAQ). 


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🚨  ACCEPT THE CALL HERE !  🚨

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NEED MORE INFO BEFORE ACCEPTING THE CALL?

CONTINUE BELOW TO SEE HOW ANTIBIOGO WORKS


Antibiogo Demo Video




Analysis of an AST plate with the Antibiogo app



A prepared and incubated Petri dish (figure a) is positioned in a simple image acquisition setup made of cardboard (figure b). We used two containers available in the laboratory as stands.


A picture of the plate is taken with a smartphone and the analysis follows the workflow described in figure c:

  • the Petri dish image is cropped and the antibiotic disks are found (figure c1);
  • the image of each antibiotic disk is fed to a ML model that identifies the antibiotic (figure c2);
  • the diameter of the inhibition zone is measured (figure c3) with an original algorithm.
  • Finally, the Expert System uses the diameters to output interpreted results (figure c4).


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To learn even more about The MSF Foundation, our commitment to data privacy and biosafety, and to satisfy further inquiry into our program, visit our FAQs.


For all questions regarding the Antibiogo Program and Antibiogo Challenge, please contact Paige Perillat-Piratoine by email at paige@jogl.io or here on JOGL at Paige Perillat-Piratoine.


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