Expressions of interest

#HDA20 | @AIDH_healthdata

We welcome all industry and clinicians to submit an abstract to the Health Data Analytics 2020 Conference.


Industry abstracts should provide delegates with practical insights into how digital health care initiatives are being used to transform the health system and improve patient outcomes.

Clinical abstracts are invited from practitioners working in a clinical environment about informatics projects aimed at improving the day-to-day delivery of patient care. Projects may focus on clinician workflows, communication, decision support, patient education and safety. Projects ideally have been implemented and evaluated in a clinical setting, and are potentially transferrable to other sites.

A key theme for Health Data Analytics is preparing for healthcare delivered in the world of artificial intelligence. How are we preparing for this massive leap in health technology, and how will we manage and protect personal data?

We are seeking abstracts to make a dynamic stream on AI with topics around:

Data analytics in the world of AI

  • Workforce
  • Machine learning
  • Genomics
  • Governance

Important Dates

Expression of interest open Now open


Expression of interest close 1 June 2020


Notify authors week beginning 22 June 2020


Authors to register by 3 July 2020

Abstract Guidelines

  • You may list authors and affiliations
  • Include a presentation title
  • Submission to be maximum 350 words. If your abstract exceeds 350 words you will need to resubmit
  • Double check spelling and grammar. Please replace American spelling with British English spelling
  • Abstract title to be in sentence case, using capitals where appropriate eg “My abstract title: An exploration of sentence structure”
  • Abstract must be submitted as a word document

Structure Abstract Covering

  1. Introduction (setting, problem/challenge to be solved)
  2. Technology Brief
  3. Implementation Processes
  4. Conclusion – outcomes and lessons learnt

Abstract Template

First AUTHORa,[1] and Second AUTHOR b
a Affiliation
b Affiliation

First paragraph.
Second paragraph.

First paragraph.
Second paragraph.

First paragraph.
Second paragraph.

First paragraph.
Second paragraph.

First Word, Second Word, etc.

[1] Corresponding Author.