Thursday, April 15, 2021
  • Setup menu at Appearance » Menus and assign menu to Top Bar Navigation
Advertisement
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News
No Result
View All Result
NikolaNews
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News
No Result
View All Result
NikolaNews
No Result
View All Result
Home Machine Learning

Federated Learning Balances Machine Learning with Patient Privacy

April 13, 2019
in Machine Learning
Federated Learning Balances Machine Learning with Patient Privacy
586
SHARES
3.3k
VIEWS
Share on FacebookShare on Twitter

Credit: Google News

April 12, 2019 – Federated learning, in which data sources for machine learning are distributed across multiple locations, is gaining traction in the healthcare industry. 

You might also like

Sailthru Announces Machine Learning Features for Improved Lifecycle Optimization

Global Machine Learning Market In-Depth Qualitative Insights & Future Growth Analysis 2021-2027 – The Courier

Seminar on Machine Learning Techniques in Banking – India Education| Global Education |Education News

Instead of centralizing data in a central server, federated learning allows patient data to remain on-premise in the hospital. This enables hospitals and other healthcare organizations to taking advantage of machine learning, while protecting patient privacy.

Federated learning can “train a model using data stored at multiple different hospitals without the data ever leaving a hospital’s premises or touching a tech company’s servers,” explained Karen Hao in a recent MIT Technology Review article.

Dig Deeper

“It does this by first training separate models at each hospital with the local data available and then sending those models to a central server to be combined into a master model,” Hao related.

When a hospital acquires more data, it can download the latest master model from the server, update it with the new data, and send it back to the server.

“Throughout the process, raw data is never exchanged—only the models, which cannot be reverse-engineered to reveal that data,” she noted.

“There is a false dichotomy between the privacy of patient data and the utility of the data to society,” Ramesh Raskar, an MIT associate professor of computer science, told MIT Technology Review. “People don’t realize the sand is shifting under their feet and that we can now in fact achieve privacy and utility at the same time.”

At the same time, federated learning has several problems that need to be worked out. For example, every hospital has to have the infrastructure and personnel for training machine-learning models, and data collection needs to be standardized across hospitals for federated learning to work.

Raskar is working on solving the problems of federated learning. One solution is called split learning in which each hospital trains separate models but only goes half way. The partial models are sent to a central server, where they are combined, and training is completed. This approach helps lessen the computational burden on hospitals.

Some companies, such as IBM Research and Paris-based startup Owkin, are working on applying federation learning to tackle healthcare challenges.

Owkin is using federated learning to predict the resistance of cancer patients to certain treatment and drugs. The startup is collaborating with U.S. and European cancer centers to use their data for its models. The company is developing a new model that predicts survival odds for a rare type of cancer based on a patient’s pathology images.

“The biggest barrier in oncology today is knowledge. It’s really amazing that we now have the power to extract that knowledge and make medical breakthrough discoveries,” Owkin Founder Thomas Clozel told MIT Technology Review.

Machine learning is one part of the broader artificial intelligence concept. A number of recent market reports predict robust growth for artificial intelligence in healthcare, ranging between a 47 percent and 50 percent compound annual growth rate.

Factors fueling the use of artificial intelligence include large and complex data sets, soaring healthcare costs, improving computing power, and declining cost of hardware.

At the same time, growth could be held back by practitioners’ reluctance to adopt AI technology, lack of skilled workers, ambiguous regulatory guidelines for medical software, and fear of AI’s impact on healthcare employment and care.

A recent report by Boston Consulting Group advised healthcare organizations to embrace artificial intelligence tools that provide clinical decision support, diagnostic imaging analysis, patient monitoring, and process automation.

“The journey to integrate AI into strategies and operations must be a sustained one. But even companies that have yet to invest in AI decisively can make some smart, low-risk moves to either enhance the positive value shifts or minimize the negative impacts,” BCG observed.

Credit: Google News

Previous Post

Julian Assange arrested by UK police, charged with hacking in the US

Next Post

Avail This Price Drop Offer On The Complete Machine Learning A to Z Bundle With Wccftech Deals

Related Posts

Sailthru Announces Machine Learning Features for Improved Lifecycle Optimization
Machine Learning

Sailthru Announces Machine Learning Features for Improved Lifecycle Optimization

April 14, 2021
Global Machine Learning Market In-Depth Qualitative Insights & Future Growth Analysis 2021-2027 – The Courier
Machine Learning

Global Machine Learning Market In-Depth Qualitative Insights & Future Growth Analysis 2021-2027 – The Courier

April 14, 2021
Seminar on Machine Learning Techniques in Banking – India Education| Global Education |Education News
Machine Learning

Seminar on Machine Learning Techniques in Banking – India Education| Global Education |Education News

April 14, 2021
Applying artificial intelligence to science education — ScienceDaily
Machine Learning

Machine learning can help slow down future pandemics — ScienceDaily

April 14, 2021
ML Ops and the Promise of Machine Learning at Scale
Machine Learning

ML Ops and the Promise of Machine Learning at Scale

April 14, 2021
Next Post
Avail This Price Drop Offer On The Complete Machine Learning A to Z Bundle With Wccftech Deals

Avail This Price Drop Offer On The Complete Machine Learning A to Z Bundle With Wccftech Deals

Leave a Reply Cancel reply

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

Recommended

Plasticity in Deep Learning: Dynamic Adaptations for AI Self-Driving Cars

Plasticity in Deep Learning: Dynamic Adaptations for AI Self-Driving Cars

January 6, 2019
Microsoft, Google Use Artificial Intelligence to Fight Hackers

Microsoft, Google Use Artificial Intelligence to Fight Hackers

January 6, 2019

Categories

  • Artificial Intelligence
  • Big Data
  • Blockchain
  • Crypto News
  • Data Science
  • Digital Marketing
  • Internet Privacy
  • Internet Security
  • Learn to Code
  • Machine Learning
  • Marketing Technology
  • Neural Networks
  • Technology Companies

Don't miss it

Microsoft Defender for Endpoint now protects unmanaged BYO devices
Internet Security

Microsoft Defender for Endpoint now protects unmanaged BYO devices

April 15, 2021
New JavaScript Exploit Can Now Carry Out DDR4 Rowhammer Attacks
Internet Privacy

New JavaScript Exploit Can Now Carry Out DDR4 Rowhammer Attacks

April 15, 2021
Sailthru Announces Machine Learning Features for Improved Lifecycle Optimization
Machine Learning

Sailthru Announces Machine Learning Features for Improved Lifecycle Optimization

April 14, 2021
Data Labeling Service — How to Get Good Training Data for ML Project? | by ByteBridge | Apr, 2021
Neural Networks

Data Labeling Service — How to Get Good Training Data for ML Project? | by ByteBridge | Apr, 2021

April 14, 2021
The Search Engine Land Awards are open: Wednesday’s daily brief
Digital Marketing

The Search Engine Land Awards are open: Wednesday’s daily brief

April 14, 2021
Six courses to build your technology skills in 2021 – IBM Developer
Technology Companies

IBM joins Eclipse Adoptium and offers free certified JDKs with Eclipse OpenJ9 – IBM Developer

April 14, 2021
NikolaNews

NikolaNews.com is an online News Portal which aims to share news about blockchain, AI, Big Data, and Data Privacy and more!

What’s New Here?

  • Microsoft Defender for Endpoint now protects unmanaged BYO devices April 15, 2021
  • New JavaScript Exploit Can Now Carry Out DDR4 Rowhammer Attacks April 15, 2021
  • Sailthru Announces Machine Learning Features for Improved Lifecycle Optimization April 14, 2021
  • Data Labeling Service — How to Get Good Training Data for ML Project? | by ByteBridge | Apr, 2021 April 14, 2021

Subscribe to get more!

© 2019 NikolaNews.com - Global Tech Updates

No Result
View All Result
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News

© 2019 NikolaNews.com - Global Tech Updates