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Tag: ai

Conversation with one of the founders of modern digital pathology

“Digital pathology has reached the point where if you don’t have digitized slides, you will not be able to do six out of ten things that other pathologists can do today.”

Dr. Anil Parwani

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Training AI to predict outcomes for cancer patients

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.

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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 the company’s HE2RNA model provides virtual spatialization of gene expression was detailed to online delegates by senior translational scientist Alberto Romagnoni who highlighted its use in clinical diagnosis. During his presentation, delegates heard how Owkin has collaborated with doctors, hospitals and academic institutions to develop the tool.

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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 the risk of recurrence, disease aggressiveness and long-term survival, according to a leading expert in the field, Professor Anant Madabhushi from Case Western Reserve University in Ohio.

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How deep learning is transforming medical imaging: image search

Five or six years ago, I was looking for a strategic direction for the KIMIA Lab. We started with the problems. We asked, ‘What problems do we have in medical imaging?’ 

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What AI Can and Can’t Do for Digital Pathology Right Now

It was fascinating to speak with Hamid Tizhoosh, Professor at the Faculty of Engineering at the University of Waterloo in Canada, Director of KIMIA Lab and keynote speaker at the 6th Digital Pathology & AI Congress: USA, about using AI to transform what is possible in medical imaging.

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Digital pathology: From over-promising to a reality check

Almost five years ago, the plan to implement a wide-ranging digital pathology approach across the Netherlands began to take shape. As more labs across the country acquire digital pathology capability, with steps to create a strong and accessible image repository and a national image exchange platform, one of the project leaders, Professor Katrien Grünberg, offered an update and spoke of some challenges that still lie ahead.

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imCMS: The door to simple, cheap, reliable bio-stratification

Bringing molecular and digital pathology closer together through a more integrative approach can lead to clear advantages for diagnostic and research workflows.

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