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The most impressive advances of digital pathology are found in oncology, where refined AI applications generate increasingly precise predictions on cancer outcomes. Digitisation facilitates data sharing and access to second opinions – and helps keeping the workspace clutter in check. 

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Article • Applications of machine learning

Training AI to predict outcomes for cancer patients

Predicting cancer outcome could help with a clinical decision regarding a patient’s treatment. In his keynote speech during the online ‘7th Digital Pathology and AI Congress: Europe’, Johan Lundin, Research Director at the Institute for ...

Article • Getting rid of the clutter

Bringing digital pathology to the hospital environment

It is a simple image of two desks in a hospital pathology department, taken a matter of months apart. But there can be few more vivid images that illustrate the changing world of pathology as the specialty forges ahead into the digital era. The ...

Article • Second opinion from afar

Telepathology: a prime application of digital pathology

Telepathology remains number one application for digital pathology, according to expert Professor Liron Pantanowitz, Professor of Pathology and Director of Anatomical Pathology at the University of Michigan. Speaking at the ‘7th Digital Pathology ...

Article • AI use in clinical diagnosis

Deep learning tool predicts tumour expression from whole slide images

A deep learning model to predict RNA-Seq expression of tumours from whole slide images was among the industry innovations outlined at the 7th Digital Pathology and AI Congress for Europe. Created by French-American start-up Owkin, the detail of how ...

Article • Digital pathology

An exciting new era for tissue microarrays

A new generation of tissue microarrays are delivering more efficient and time-effective solutions to answering complex clinical and scientific questions. Sitting at the core of this new approach is digital pathology, allowing specific and targeted ...

Article • Machine learning advances diagnostics and prognostics

Computerized image analysis can predict cancer outcomes

The advent of digital pathology is offering a unique opportunity to develop computerized image analysis methods to diagnose disease and predict outcomes for cancer patients from histopathology tissue sections. Such advances can help predict risk of ...

 

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