Training AI to predict outcomes for cancer patients
Posted 30th March 2021 by Nicholas Noakes
Predicting the outcome of cancer can help the clinical decision-making process related to a patient’s treatment. The potential for Artificial Intelligence (AI) to support this was a key facet of the final keynote speech to the online 7th Digital Pathology and AI Congress: Europe, by Johan Lundin, Research Director at the Institute for Molecular Medicine Finland (FIMM) at the University of Helsinki and Professor of Medical Technology at Karolinska Institutet.
Quantitative Image Analysis Guidelines: An Open letter from Liron Pantanowitz
Posted 20th October 2017 by Jane Williams
Dear Colleagues,
There has been a steady increase in the adoption of Quantitative Image Analysis (QIA) for diagnostic purposes, especially for breast biomarker testing.
Process Control for Immunohistochemistry Staining Procedures
Posted 11th October 2017 by Jane Williams
An extensively used technique for evaluating the expression of tissue antigens and their behaviour is known as immunohistochemistry (IHC). In this technique, the primary antibody raised against the specific antigen and a secondary antibody against the primary one is used for detecting specific targets of clinical relevance. IHC has the greatest impact on diagnostic pathology compared to any other technique. Although modern methods of flow cytometry and molecular diagnosis have also contributed enormously, IHC still remains the most relevant solution for various pathological diagnostic problems.
