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Democratizing Medicine with AI

5/11/2022

 
The Open Source Image Consortium (OSIC) is working to democratize medicine by giving OSIC clinicians and members everywhere the ability to access and benefit from the same technology and information as those affiliated with major research centers. “If we can figure out how to drive collaboration in healthcare, we will change the paradigm,” says Executive Director Elizabeth Estes. 
Read More on Forbes »

A Bold Approach: Improving Rare Disease Treatment and Patient Care through Data Transparency

3/11/2022

 
For decades, the healthcare industry has lacked a long list of elements necessary to understand the nature of hundreds of rare diseases — industry cohesiveness and data transparency chief amongst them. With the help of PwC and Microsoft, one pioneering group of minds may have finally found a key part of the solution: an open-source approach to medical research.
Read More on WIRED »

How AI is Creating a Hopeful Future for Patients

3/11/2022

 
“We have a lot of smart, motivated, dedicated people together who want to see these patients have a different path. The technology is there for personalized medicine. The technology is there to make advances in rare disease,” says Elizabeth Estes, OSIC executive director.
Watch the WIRED Video »

Forging a New Path to Manage Rare Diseases, Built on Cloud Technology

3/9/2022

 
A discussion with the Open Source Imaging Consortium, Microsoft and PwC: See how data and analytics, AI and cloud will reshape the future of healthcare.
Watch the Webcast »

A Brighter Future for Medicine with Healthcare Technology

3/9/2022

 
A first-of-its-kind open source medical imaging and data repository platform is highlighting new possibilities to help improve the speed and accuracy of diagnosis and help patients, providers and researchers better manage the disease.
Read the case study »

OSIC Opens Large Database to Aid Research Into PF, Other ILDs

9/15/2021

 
A large and multi-ethnic database, reported to be the first of its kind for rare lung diseases, is now compiling real-world clinical and imaging data on people with pulmonary fibrosis (PF) and other interstitial lung diseases (ILDs) from centers across the globe.
Read more on Pulmonary Fibrosis News »

First-of-its-Kind, Global Data Repository for Interstitial Lung Diseases Launches Through Academic and Industry Collaborative

9/7/2021

 
The highly-anticipated Open Source Imaging Consortium (OSIC) database is driven by global experts in pulmonology, radiology and artificial intelligence, and is the most diverse and largest for rare fibrotic lung diseases
MEDIA CONTACT
​Theresa Hennessey Barcy
theresa@tmhpublicrelations.com
​773-960-7276
HOLLAND, Mich., Tuesday, September 7, 2021 – The Open Source Imaging Consortium (OSIC) today announced the launch of its global, data-rich repository of anonymized HRCT scans and clinical information regarding interstitial lung diseases (ILDs). This first-of-its-kind database is the world’s largest and most diverse, with a plethora of real world clinical and imaging data that is both multi-ethnic and multi-center. The OSIC Data Repository currently houses close to 1,500 anonymized and quality-controlled scans with accompanying data, and has an additional 5,000 in the quality control queue. It is on track to reach its goal of 15,000 anonymized scans, available to OSIC members, by first quarter 2022.​

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Open Source Imaging Consortium (OSIC) Announces Winners of its $55,000 Kaggle Challenge

12/14/2020

 
AI-Focused Competition Called on the World’s Brightest Data Science Minds
to Predict Lung Function Decline by Using Machine Learning
MEDIA CONTACT
​Theresa Hennessey Barcy
theresa@tmhpublicrelations.com
​773-960-7276
HOLLAND, Mich., Monday, December 14, 2020 – The Open Source Imaging Consortium (OSIC) announced today the winners of its $55,000 OSIC Pulmonary Fibrosis Progression Challenge, the first-ever computational challenge for interstitial lung diseases (ILDs). The AI-focused competition was administered by Kaggle, the world’s largest data science community platform, and asked participants to use machine learning to predict lung function decline in people living with pulmonary fibrosis.

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Open Source Imaging Consortium (OSIC) Launches $55,000 AI Competition to Help Pulmonary Fibrosis Patients

7/7/2020

 
The OSIC Pulmonary Fibrosis Progression Will Challenge the World’s Brightest
Data Science Minds to Predict Lung Function Decline by Using Machine Learning

MEDIA CONTACT
​Theresa Hennessey Barcy
theresa@tmhpublicrelations.com
​773-960-7276
HOLLAND, Mich., Tuesday, July 7, 2020 -- The Open Source Imaging Consortium (OSIC) announced today the launch of the $55,000 OSIC Pulmonary Fibrosis Progression, an AI-focused challenge to predict lung function decline in people living with pulmonary fibrosis. The competition is administered by Kaggle, the world’s largest data science community platform, and runs through October 6, 2020.

Read More

Interstitial Lung Disease (ILD) Experts and Advocates Announce Formation of Open Source Imaging Consortium (OSIC)

5/22/2019

 
Global, Not-for-Profit, Collaborative Effort Focuses on Digital Imaging and Machine Learning to Enable Rapid Advances in the Fight against Idiopathic Pulmonary Fibrosis (IPF), Fibrosing ILDs, and Other Respiratory Diseases including Emphysematous Conditions ​
MEDIA CONTACT
​Theresa Hennessey Barcy
theresa@tmhpublicrelations.com
​773-960-7276
HOLLAND, Mich., Wednesday, May 22, 2019 — An international group of leading experts and advocates in the fight against idiopathic pulmonary fibrosis (IPF), fibrosing interstitial lung diseases (ILDs), and other respiratory diseases including emphysematous conditions announced today the formation of the Open Source Imaging Consortium (OSIC). This global, not-for-profit organization is a cooperative and open source effort between academia, industry and philanthropy to enable rapid advances in the detection and diagnosis of these conditions through digital imaging and machine learning.

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  • About OSIC ▾
    • Our Goals
    • Board of Directors
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  • Data Repository ▾
    • About the Data Repository
    • Data Repository Support
  • Challenges ▾
    • Kaggle Challenge #1
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