Posted 18th September 2019 by Joshua Sewell
I can recall clearly the pathologists coming to lecture our medical school class our second year in 1993.
Most of them felt compelled to tell us, “Pathology is a lot of fun, you can make a good living, but don’t go into it, there aren’t any jobs.”
Posted 11th September 2019 by Joshua Sewell
Ahead of his presentation at the 6th Digital Pathology and AI Congress: Europe, we spoke to Andrew Janowczyk about his work creating scalable data analysis techniques to facilitate cancer research through the development of open-source Digital Pathology tools.
Posted 28th August 2019 by Jane Williams
Following the 5th Digital Pathology & AI Congress: USA, we have made the following presentation slides available from Iman Hajirasouliha, Kim Solez and Mrinal Mandal.
Posted 10th May 2019 by Joshua Sewell
Unsurprisingly, there is a lot of hype surrounding AI. Available deep learning packages make it so easy to create models and so we can expect lots of them to emerge. Anyone able to access sufficiently labelled data can start building models.
Posted 17th April 2019 by Joshua Sewell
David Snead is Consultant Histopathologist and Clinical lead for Coventry and Warwickshire Pathology Services (CWPS), a network of labs hosted by University Hospitals of Coventry and Warwickshire NHS Trust. As head of the UHCW Digital Pathology Centre of Excellence, he is now heavily involved in the Pathology image data Lake for Analytics, Knowledge, and Education (PathLAKE).
Posted 5th April 2019 by Joshua Sewell
Aiforia Technologies is a medical AI software company seeking to transform clinical pathology and medical research by bringing deep learning AI to assist and augment human experts in medical image analysis.
We had the chance to ask CEO Kaisa Helminen about AI in healthcare and Aiforia’s newest platform.
Posted 1st March 2019 by Joshua Sewell
This is the second of a two-part blog post. In his first post, Liron wrote on embedding AI in Digital Pathology workflows.
Digital Pathology AI apps are certainly feasible, but exactly when they will be ready for clinical use is less clear.
There are potentially hundreds or thousands of algorithms that will need to be developed. Currently, there are only a handful of algorithms that are approved by regulatory bodies for clinical practice, so we’ve got a long way to go.
Posted 22nd February 2019 by Joshua Sewell
This is an exciting time in pathology: now that digital pathology is mature, we have noticed an uptake in a lot of AI start-up companies. Most of the algorithms have been developed on a research basis or in a test environment, and only recently applied. What follows is a summary of the work we are doing at the University of Pittsburgh Medical Center testing these AI apps, and some of the questions arising therefrom.