AIMS: The objective of this study was to develop and validate an open-source digital pathology tool, QuPath, to automatically quantify CD138-positive bone marrow plasma cells (BMPCs).
Since 2007, we have gradually been building up infrastructure for digital pathology, starting with a whole slide scanner park to build up a digital archive to streamline doing multidisciplinary meetings, student teaching and research, culminating in ...
During the last decade, a dramatic rise in the development and application of artificial intelligence (AI) tools for use in pathology services has occurred. This trend is often expected to continue and reshape the field of pathology in the coming yea...
The measures to control the COVID-19 outbreak will likely remain a feature of our working lives until a suitable vaccine or treatment is found. The pandemic has had a substantial impact on clinical services, including cancer pathways. Pathologists ar...
AIMS: Morphological recognition of red blood cells infected with malaria parasites is an important task in the laboratory practice. Nowadays, there is a lack of specific automated systems able to differentiate malaria with respect to other red blood ...
AIMS: Morphological differentiation among different blast cell lineages is a difficult task and there is a lack of automated analysers able to recognise these abnormal cells. This study aims to develop a machine learning approach to predict the diagn...
AIMS: Red blood cell (RBC) lysis resistance interferes with white blood cell (WBC) count and differential; still, its detection relies on the identification of an abnormal scattergram, and this is not clearly adverted by specific flags in the Beckman...
AIMS: To evaluate if a deep learning algorithm can be trained to identify tumour-infiltrating lymphocytes (TILs) in tissue samples of testicular germ cell tumours and to assess whether the TIL counts correlate with relapse status of the patient.