Today, Thursday 5 May, is being celebrated worldwide as the International Day of the Midwife, organised by the International Confederation of Midwives.
The White Ribbon Alliance ran a campaign called Midwives’ Voices, Midwives’ Demands, where they asked more than 56,000 midwives and health workers around the world about what they want and need to better serve women in their care and for themselves as midwives.
Fast Data Science - London
We have set up an interactive dashboard for White Ribbon Alliance which allows users to explore the respondents’ demands in free text, and visualise them into handy charts, word clouds, and a map view. The dashboard used natural language processing techniques such as supervised learning and text classifiers to categorise the responses into groups.
Screenshot of the Midwives’ Voices, Midwives’ Demands interactive NLP dashboard. Click here to explore the dashboard.
The White Ribbon Alliance has launched the dashboard today to celebrate the International Day of the Midwife, and are hoping to raise awareness of the need to improve the status of midwifery in healthcare systems today.
The Midwives’ Voices, Midwives’ Demands follows on from the groundbreaking What Women Want campaign, where White Ribbon Alliance collected 1.2 million responses from women around the world about their healthcare needs. You can explore the What Women Want campaign dashboard here.
If you would like an interactive NLP dashboard for your project, you can read more about what we can achieve here.
Unleash the potential of your NLP projects with the right talent. Post your job with us and attract candidates who are as passionate about natural language processing.
Hire NLP Experts
When can lawyers, litigants in person, and expert witnesses use AI in court documents? In the last few years in the UK, the USA, Canada, Ireland and other jurisdictions, cases have been reported where submissions were made to a court where the author of a document used generative AI tools such as ChatGPT to create those documents. This has wasted court time, resulted in submissions being rejected or even resulted in changes to cost awards.
A person has recently returned from a camping trip and has a fever. Should a doctor diagnose flu or Lyme disease? Would this be any different if they had not mentioned their camping trip? Here’s how LLMs differ from human experts.
How can you predict customer churn using machine learning and AI? In an earlier blog post, I introduced the concept of customer churn. Here, I’d like to dive into customer churn prediction in more detail and show how we can easily and simply use AI to predict customer churn.
What we can do for you
