Liwaiwai Liwaiwai
  • /
  • Artificial Intelligence
  • Machine Learning
  • Robotics
  • Engineering
    • Architecture
    • Design
    • Software
    • Hybrid Cloud
    • Data
  • About
Liwaiwai Liwaiwai
  • /
  • Artificial Intelligence
  • Machine Learning
  • Robotics
  • Engineering
    • Architecture
    • Design
    • Software
    • Hybrid Cloud
    • Data
  • About
  • Artificial Intelligence

Intel Works With University Of Pennsylvania In Using Privacy-Preserving AI To Identify Brain Tumors

  • May 14, 2020
  • relay

federated learning explainer

 

Intel Labs and the Perelman School of Medicine at the University of Pennsylvania (Penn Medicine) are co-developing technology to enable a federation of 29 international healthcare and research institutions led by Penn Medicine to train artificial intelligence (AI) models that identify brain tumors using a privacy-preserving technique called federated learning. Penn Medicine’s work is funded by the Informatics Technology for Cancer Research (ITCR) program of the National Cancer Institute (NCI) of the National Institutes of Health (NIH), through a three-year, $1.2 million grant awarded to principal investigator Dr. Spyridon Bakas at the Center for Biomedical Image Computing and Analytics (CBICA) of the University of Pennsylvania.

“AI shows great promise for the early detection of brain tumors, but it will require more data than any single medical center holds to reach its full potential. Using Intel software and hardware and support from some of Intel Labs’ brightest minds, we are working with the University of Pennsylvania and a federation of 29 collaborating medical centers to advance the identification of brain tumors while protecting sensitive patient data.”
– Jason Martin, principal engineer, Intel Labs

How It Works

Penn Medicine and 29 healthcare and research institutions from the United States, Canada, the United Kingdom, Germany, the Netherlands, Switzerland and India will use federated learning, which is a distributed machine learning approach that enables organizations to collaborate on deep learning projects without sharing patient data.

Penn Medicine and Intel Labs were the first to publish a paper on federated learning in the medical imaging domain, particularly demonstrating that the federated learning method could train a model to over 99% of the accuracy of a model trained in the traditional, non-private method. This paper was originally presented at the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2018 in Granada, Spain. The new work will leverage Intel software and hardware to implement federated learning in a manner that provides additional privacy protection to both the model and the data.

Read More  Intel, Habana Labs And Hugging Face Advance Deep Learning Software

“It is widely accepted by our scientific community that machine learning training requires ample and diverse data that no single institution can hold,” Bakas said. “We are coordinating a federation of 29 collaborating international healthcare and research institutions, which will be able to train state-of-the-art AI models for healthcare, using privacy-preserving machine learning technologies, including federated learning. This year, the federation will begin developing algorithms that identify brain tumors from a greatly expanded version of the International Brain Tumor Segmentation (BraTS) challenge dataset. This federation will allow medical researchers access to vastly greater amounts of healthcare data while protecting the security of that data.”

Why It Matters

According to the American Brain Tumor Association (ABTA), nearly 80,000 people will be diagnosed with a brain tumor this year, with more than 4,600 of them being children. In order to train and build a model to detect a brain tumor that could aid in early detection and better outcomes, researchers need access to large amounts of relevant medical data. However, it is essential that the data remain private and protected, which is where federated learning with Intel technology comes in. By utilizing this approach, researchers from all partner organizations will be able to work together on building and training an algorithm to detect a brain tumor while protecting sensitive medical data.

What’s Next

In 2020, Penn and the 29 international healthcare and research institutions will use Intel’s federated learning hardware and software to produce a new state-of-the-art AI model that is trained on the largest brain tumor dataset to date — all without sensitive patient data leaving the individual collaborators. The subset of collaborating institutions expected to participate in initiating the first phase of this federation includes the Hospital of the University of Pennsylvania, Washington University in St. Louis, the University of Pittsburgh Medical Center, Vanderbilt University, Queen’s University, Technical University of Munich, University of Bern, King’s College London and Tata Memorial Hospital.

Read More  Mobileye, Geely To Offer Most Robust Driver-Assistance Features
relay

Related Topics
  • American Brain Tumor Association
  • Brain Tumor
  • Informatics Technology for Cancer Research
  • Intel
  • University of Pennsylvania
You May Also Like
View Post
  • Artificial Intelligence
  • Software
  • Technology

Bard And ChatGPT — A Head To Head Comparison

  • March 31, 2023
View Post
  • Artificial Intelligence
  • Platforms

Modernize Your Apps And Accelerate Business Growth With AI

  • March 31, 2023
View Post
  • Artificial Intelligence
  • Technology

Unlocking The Secrets Of ChatGPT: Tips And Tricks For Optimizing Your AI Prompts

  • March 29, 2023
View Post
  • Artificial Intelligence
  • Technology

Try Bard And Share Your Feedback

  • March 29, 2023
View Post
  • Artificial Intelligence
  • Data
  • Data Science
  • Machine Learning
  • Technology

Google Data Cloud & AI Summit : In Less Than 12 Hours From Now

  • March 29, 2023
View Post
  • Artificial Intelligence
  • Technology

Talking Cars: The Role Of Conversational AI In Shaping The Future Of Automobiles

  • March 28, 2023
View Post
  • Artificial Intelligence
  • Tools

Document AI Introduces Powerful New Custom Document Classifier To Automate Document Processing

  • March 28, 2023
View Post
  • Artificial Intelligence
  • Design
  • Practices

How AI Can Improve Digital Security

  • March 27, 2023

Leave a Reply

Your email address will not be published. Required fields are marked *

Stay Connected!
LATEST
  • 1
    Bard And ChatGPT — A Head To Head Comparison
    • March 31, 2023
  • 2
    Modernize Your Apps And Accelerate Business Growth With AI
    • March 31, 2023
  • 3
    Why Your Open Source Project Needs A Content Strategy
    • March 31, 2023
  • 4
    From Raw Data To Actionable Insights: The Power Of Data Aggregation
    • March 30, 2023
  • 5
    Effective Strategies To Closing The Data-Value Gap
    • March 30, 2023
  • 6
    Unlocking The Secrets Of ChatGPT: Tips And Tricks For Optimizing Your AI Prompts
    • March 29, 2023
  • 7
    Try Bard And Share Your Feedback
    • March 29, 2023
  • 8
    Google Data Cloud & AI Summit : In Less Than 12 Hours From Now
    • March 29, 2023
  • 9
    Talking Cars: The Role Of Conversational AI In Shaping The Future Of Automobiles
    • March 28, 2023
  • 10
    Document AI Introduces Powerful New Custom Document Classifier To Automate Document Processing
    • March 28, 2023

about
About
Hello World!

We are liwaiwai.com. Created by programmers for programmers.

Our site aims to provide materials, guides, programming how-tos, and resources relating to artificial intelligence, machine learning and the likes.

We would like to hear from you.

If you have any questions, enquiries or would like to sponsor content, kindly reach out to us at:

[email protected]

Live long & prosper!
Most Popular
  • 1
    Introducing GPT-4 in Azure OpenAI Service
    • March 21, 2023
  • 2
    How AI Can Improve Digital Security
    • March 27, 2023
  • 3
    ChatGPT 4.0 Finally Gets A Joke
    • March 27, 2023
  • 4
    Mr. Cooper Is Improving The Home-buyer Experience With AI And ML
    • March 24, 2023
  • 5
    My First Pull Request At Age 14
    • March 24, 2023
  • /
  • Artificial Intelligence
  • Machine Learning
  • Robotics
  • Engineering
  • About

Input your search keywords and press Enter.