• Skip to main content
  • Skip to header right navigation
  • Skip to site footer
CCAIM

CCAIM

Novel AI to transform healthcare

  • Home
  • About
    • Our Aims
    • ISAB Report
  • People
    • Leadership
    • Faculty
    • Associate Faculty
    • Joint Steering Committee
    • Independent Scientific Advisory Board
    • Staff
    • Our students
    • Affiliated clinical PhD Students
    • Visitors
  • Research
    • Papers
    • Breakthroughs
    • Software
      • AutoPrognosis
      • HyperImpute
      • Interpretability Suite
      • Synthcity
      • TemporAI
    • Demonstrators
    • Research Update: COVID-19
    • Blog
  • News
    • Latest News
    • COVID-19 News
  • Events
    • Seminar Series
    • WeCREATE
    • Inaugural Event
    • AI Clinic 2023
    • AI Clinic 2022
  • Summer School
    • Summer School 2023
      • Participate
      • Program
      • Topics
      • Industry
      • FAQ
    • Summer School 2022
  • Get involved
    • PhD Programmes
    • Clinical PhD Position
    • Partners
    • Connect

Cystic fibrosis

External Validity of Machine Learning-based Prognostic Scores for Cystic Fibrosis – new publication

21 December 2022 by Andreas Bedorf

A paper recently accepted for publication by PLOS Digital Health explores machine-learning based prognostic scores and their validity when applied to demographically different patient cohorts: the ‘external validity’. The publication …

Read moreExternal Validity of Machine Learning-based Prognostic Scores for Cystic Fibrosis – new publication

Ability of multi-drug resistant infection to evolve within cystic fibrosis patients highlights need for rapid treatment

30 April 2021 by Navneet Gidda

Scientists have been able to track how a multi-drug resistant organism is able to evolve and spread widely among cystic fibrosis patients – showing that it can evolve rapidly within …

Read moreAbility of multi-drug resistant infection to evolve within cystic fibrosis patients highlights need for rapid treatment

Empowering people with CF to take control with smart self-monitoring

27 October 2020 by boss

CCAIM Co-Director Andres Floto, pictured above outside Royal Papworth Hospital in Cambridge, is leading a study on home monitoring for people with cystic fibrosis. The research is central to Project …

Read moreEmpowering people with CF to take control with smart self-monitoring

Machine learning comes of age in cystic fibrosis

21 October 2020 by Sean O'Neill

World-leading AI technology developed at the University of Cambridge by the directors of the Cambridge Centre for AI in Medicine and their colleagues offers a glimpse of the future of …

Read moreMachine learning comes of age in cystic fibrosis

Advances in machine learning for cystic fibrosis revealed at the North American CF Conference 2020

7 October 2020 by Sean O'Neill

World-leading machine learning (ML) technology developed at the University of Cambridge promises powerful new prediction and analytical tools to support the clinical care of individuals with the life-limiting condition. The …

Read moreAdvances in machine learning for cystic fibrosis revealed at the North American CF Conference 2020

Navigation

Home

News

About

University of Cambridge

  • University A-Z
  • Contact the University
  • Accessibility
  • Data Protection
  • Terms and conditions

Newsletter

Sign-up for updates on our research.

Follow us

  • Twitter
  • LinkedIn
  • YouTube

Copyright © 2023 CCAIM

Return to top

We are using cookies to give you the best experience on our website.

You can find out more about which cookies we are using or switch them off in settings.

CCAIM
Privacy Overview

This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.

Strictly Necessary Cookies

Strictly Necessary Cookie should be enabled at all times so that we can save your preferences for cookie settings.

If you disable this cookie, we will not be able to save your preferences. This means that every time you visit this website you will need to enable or disable cookies again.

3rd Party Cookies

This website uses Google Analytics to collect anonymous information such as the number of visitors to the site, and the most popular pages.

Keeping this cookie enabled helps us to improve our website.

Please enable Strictly Necessary Cookies first so that we can save your preferences!