AI

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Supervised learning approach

A new deep learning-based algorithm to predict relapse-free survival in papillary thyroid carcinoma

The tall cell variant (TCV) is an aggressive subtype of papillary thyroid carcinoma (PTC). Sebastian Stenman, researcher from the Institute for Molecular Medicine, and the Department of Pathology at the University of Helsinki, Finland, is developing and training a deep learning algorithm using supervised learning to detect and quantify the proportion of tall cells in PTC.

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Malignant tumour management

’Our machine learning model achieved 88.9% accuracy in predicting the sarcoma-specific survival rate’

Clinical management of soft tissue sarcoma is particularly challenging. Dr Sebastian Foersch, researcher at the Institute of Pathology at the University Medical Center in Mainz, Germany, has used a deep learning model for diagnosis and prognosis prediction of soft tissue sarcoma using conventional histopathology slides.

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Article • AI provides prognostic information

Next-generation deep learning models predict cancer survival

Deaths from cancer are currently estimated at 10 million each year worldwide. Conventional cancer staging systems aim to categorize patients into different groups with distinct outcomes. ‘However, even within a specific stage, there is often substantial variation in patient outcomes,’ Markus Plass, academic researcher from the Medical University of Graz, Austria, explained to Healthcare in…

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Article • Possibilities and risks

AI in cardiology: so much is feasible – but is everything useful?

It might sound like science fiction but it is reality in cardiology: with the help of artificial intelligence (AI) physicians can recognize from a patient’s headshot whether the person is suffering from coronary artery disease and is therefore at risk of myocardial infarction. But is that knowledge really useful? Professor Dr David Duncker calls for a differentiated and careful assessment of…

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Article • Imaging biomarkers, AI support and beyond

New tools for Covid-19 assessment

As knowledge about Covid-19 advances, so does the arsenal of techniques to predict, diagnose and follow up on the disease. At ECR, researchers presented a range of promising imaging modalities to keep track of Covid-19 symptoms, severity, and mortality, often including AI support to enhance or accelerate diagnostics.

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