Thursday, February 25, 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 Artificial Intelligence

Examining Potential of AI to Assist in Childbirth

January 16, 2019
in Artificial Intelligence
Examining Potential of AI to Assist in Childbirth
586
SHARES
3.3k
VIEWS
Share on FacebookShare on Twitter

Credit: AI Trends


You might also like

Misclassifying A Snowman As A Pedestrian Is Troublesome For AI Autonomous Cars 

Working on Open Source AI Project to Tune Models 

Guidelines for Getting Started with AIOps 

Instead of looking up at the sky to see whether you need an umbrella, people increasingly ask virtual assistants such as Alexa. And they may be wise to do so. AI methods are powerful – capable of anything from analysing astrophysical data to detecting tumours or helping to manage diabetes. An algorithm that analyses shopping patterns recently detected that a teenage girl was pregnant, earlier than her father did. So could childbirth be next for Al?

The most popular AI subset is “machine learning”, which allows a machine to learn a task without being explicitly programmed. This is achieved by algorithms that are designed with the ability to discover relationships within large amounts of data.

Just imagine an AI system that can continuously read maternal and fetal movements, breathing patterns and bio-signals such as heart rate or blood pressure – and reliably identify crucial individual patterns in the physiology, emotions and behaviours of both mothers and foetuses – during childbirth. Through learning day by day, it would get more accurate at determining which combination of patterns would lead to which outcome. Could such a system be used to suggest what to do during labour, minute by minute, with excellent levels of accuracy – including whether to go ahead with a vaginal birth or opt for a caesarean section?

Maybe this could even reduce unnecessary interventions and maternal mortality, in line with WHO recommendations. If a simple reduction in interventions is the aim, AI could be very promising, in theory.

Some supporters will say that such a system would save lives and taxpayers’ money. Others will be horrified at the thought, feeling that it will result in a total loss of human companionship in labour – and of midwifery and obstetric skills and practice.

Fact or fiction?

But how close are we actually to having AI involved in childbirth – and do we know whether it would be beneficial?

A group of researchers from MIT have already developed an AI robot that can assist in a labour room. In their study involving doctors and nurses, they found that the robot’s recommendations were accepted 90% of the time and that the number of errors were similar whether the robot was there or not. On that basis they suggested it should be safe and efficient to use AI during childbirth.

However, this also raises the question – if the technology is no better than human expertise, why would we use it? Especially as humans pick up a range of subtle cues that machines cannot perceive. For example, a clinical trial called INFANT showed that the use of software that was designed to improve the decision making of midwives and obstetricians for women who had continuous electronic fetal monitoring during labour did not improve clinical outcome when compared to expert judgement.

So, it may be some time before AI is rolled out in maternity units. But we cannot ignore the writing on the wall – the potential for totally AI supported birth is not so very fantastical.

Emotional support

But birth, the beginning of life, is not a transactional enterprise that only requires monitoring and measuring to be both safe and fulfilling. It is an interaction story between the woman, her baby, her partner, labour supporters and healthcare providers. For most women around the world, it is a profoundly important experience that has an impact on parenting and self-esteem – lasting way beyond the moment of birth.

It was recently recognised that caring companionship and human emotional and psychological support not only improve birth health outcomes for both women and infants, but could have long term effects into newborn’s adult life. And current versions of AI are not actually that good at understanding human emotions or talking to people.

As we are focusing more and more on the prioritisation of measuring, monitoring, counting and recording in labour over simple human interaction, and as we fall more and more in love with our personal technology devices, there is a risk we could lose sight of what matters for human well-being in a range of areas. In fact, we are making it easier and easier to translate childbirth expertise into an Alexa-style birth assistant interface.

What will happen to women and babies if, as a result, AI one day becomes so smart that it controls us? Maybe, if AI could be used as an aid for skilled and caring birth professionals and childbearing women – rather than as the ultimate decision maker – it could contribute to the best and safest experience for each woman and her baby.

Read the source article in The Conversation.

Credit: AI Trends By: John Desmond

Previous Post

Steam Will Use Machine Learning for Game Recommendations | News & Opinion

Next Post

New Ethereum version postponed after discovery of serious security flaw

Related Posts

Misclassifying A Snowman As A Pedestrian Is Troublesome For AI Autonomous Cars 
Artificial Intelligence

Misclassifying A Snowman As A Pedestrian Is Troublesome For AI Autonomous Cars 

February 19, 2021
Working on Open Source AI Project to Tune Models 
Artificial Intelligence

Working on Open Source AI Project to Tune Models 

February 19, 2021
State of the Market: What AI Implementations Are in Place and Underway
Artificial Intelligence

Guidelines for Getting Started with AIOps 

February 19, 2021
Volkswagen Collaborating with Microsoft to Build Automated Driving Platform 
Artificial Intelligence

Volkswagen Collaborating with Microsoft to Build Automated Driving Platform 

February 19, 2021
Rule-Based AI vs. Machine Learning for Development – Which is Best? 
Artificial Intelligence

Rule-Based AI vs. Machine Learning for Development – Which is Best? 

February 19, 2021
Next Post
New Ethereum version postponed after discovery of serious security flaw

New Ethereum version postponed after discovery of serious security flaw

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

More than 6,700 VMware servers exposed online and vulnerable to major new bug
Internet Security

More than 6,700 VMware servers exposed online and vulnerable to major new bug

February 25, 2021
Everything You Need to Know About Evolving Threat of Ransomware
Internet Privacy

Everything You Need to Know About Evolving Threat of Ransomware

February 25, 2021
Machine learning speeding up patent classifications at USPTO
Machine Learning

Machine learning speeding up patent classifications at USPTO

February 25, 2021
How to Make Data Annotation More Efficient? | by ByteBridge | Feb, 2021
Neural Networks

How to Make Data Annotation More Efficient? | by ByteBridge | Feb, 2021

February 25, 2021
How to Nail Virtual and Digital Communication
Marketing Technology

How to Nail Virtual and Digital Communication

February 25, 2021
Google funds Linux kernel developers to work exclusively on security
Internet Security

Google funds Linux kernel developers to work exclusively on security

February 25, 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?

  • More than 6,700 VMware servers exposed online and vulnerable to major new bug February 25, 2021
  • Everything You Need to Know About Evolving Threat of Ransomware February 25, 2021
  • Machine learning speeding up patent classifications at USPTO February 25, 2021
  • How to Make Data Annotation More Efficient? | by ByteBridge | Feb, 2021 February 25, 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