Last week marked the fourth Informatics Summit from the American Medical Informatics Association (AMIA). The meeting provided a fantastic opportunity for members of our Informatics and Data Science practice to stay up to date with the latest developments in the fields of artificial intelligence (AI), natural language processing and machine learning in the context of healthcare.
The AMIA 2021 Virtual Informatics Summit came to a close last Thursday after 4 days of dynamic presentations on clinical research, implementation research, data science and bioinformatics. More than 500 attendees from 17 countries attended the event, which was composed of 55 sessions including plenary presentations, Ignite-style talks, panel sessions and workshops given by speakers from leading US research centres such as Stanford University, Harvard University and Massachusetts Institute of Technology.
The summit was opened by keynote speaker Dr Ned Sharpless, Director of the US National Cancer Institute, who discussed how medical informatics is changing the landscape of cancer research by helping to optimize precision treatment, support diagnosis and predict treatment responses. The event was then closed by Abigail Echo-Hawk of the Urban Indian Health Institute and Seattle Indian Health Board, who inspired with her talk on inequity in healthcare and data among tribal populations, specifically American Indians and Alaska Natives, owing to issues such as implicit bias and racial misclassification.
Our attendance at the summit was primarily to understand how informatics can be applied in the context of the pharmaceutical industry and medical communications, to better serve our clients in navigating this dynamic and complex field. Here are our key learnings.
- AI techniques have evolved over the last decade and many are reaching levels of maturity that mean they can be implemented in real-life situations, including (in some cases) those relating to healthcare; however, pharma and healthcare remain among the most highly regulated and risk-averse industries, so many of the AI advances need to evolve even further to become more transparent and explainable.
- If AI and machine learning models remain a ‘black box’ and are unable to generate actionable insights, they will never be accepted by the healthcare community. Therefore, at a time when AI is escaping research labs and academic centres to enter the real world, explainable AI (XAI) is a concept that has never been more important. As medical communications experts with a specialist Informatics and Data Science practice, we believe we can add real value for our clients here.
- More data does not necessarily mean better insights: the insights generated from AI models are only as good as the data used to build them. An awareness of what data are available to train models and how they can be accessed is critical to success.
- Ethics, bias and equity are vital considerations for the safe, fair and effective practice of informatics, particularly in healthcare. All corners of the general population must be appropriately represented in the data used for any AI technology.
We are very much looking forward to attending the AMIA 2021 Annual Symposium at the end of October, as well as next year’s Informatics Summit in March!
Contact us for more information on our Informatics and Data Science Practice.
About AMIA
AMIA is a community of more than 5600 subject-matter experts in the science and practice of informatics as it relates to clinical care, research, education and policy. Individual members include clinicians, researchers, biomedical librarians, students, policymakers, developers and industry professionals. AMIA’s community is committed to the vision of a world where informatics transforms people’s care and provides a ‘professional home’ that supports development of the informaticians of today and tomorrow.
