AI

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Sponsored • Digital solutions for radiology

How to accelerate healthcare innovation in AI

Tapping the thriving Radiology AI ecosystem, Bayer recently announced three collaboration agreements for its digital platform, Calantic Digital Solutions, as well as an AI accelerator program.

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Article • Radiology & artificial intelligence

How to integrate AI in the clinical workflow: 7 lessons

In radiology, it is not about if but about when artificial intelligence (AI) will be used, said Professor Dr Tim Leiner of Utrecht University Medical Center at this year’s European Congress of Radiology in Vienna. For all those who are new to AI, the Dutch radiologist gave an overview of the lessons he and his team have learnt so far.

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Article • AI-based personalized medical care

I³lung: EU launches lung cancer initiative

This summer, The European Commission launched I3lung, a new research initiative as a part of Horizon Europe, the EU’s research and innovation program. This research initiative aims to create a cutting-edge, decision-making tool to help clinicians and patients select the best lung cancer treatment based on each patient’s specific needs and circumstances.

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Article • Visceral imaging

Endosonography: AI takes on the “supreme discipline”

Endosonography poses unique challenges for medical professionals, because two demanding disciplines have to be mastered at the same time. The use of artificial intelligence (AI) could help speed up the notoriously slow learning curve of the procedure, says Prof Dr Christoph F. Dietrich. At the Visceral Medicine Congress in Hamburg, the expert explained how AI can help endosonography achieve…

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Article • Targeted Real-time Early Warning System for hospitals

Early detection of sepsis with the help of AI

Sepsis, a life-threatening, systemic, toxic bodily reaction to infection, is often difficult to detect in its early stages. Its symptoms, including fever, shortness of breath, rapid heart rate, and confusion, are associated with many medical conditions of hospitalized patients. But if not treated rapidly, a patient may die. The Targeted Real-time Early Warning System (TREWS) for sepsis detection…

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Article • Diagnostic assistant systems

AI in endoscopy: helper, trainer – influencer?

Artificial intelligence (AI) is increasing its foothold in endoscopy. Although the algorithms often detect pathologies faster than humans, their use also generates new problems. PD Dr Alexander Hann from the University Hospital Würzburg points out that the use of AI helpers can affect not only the reporting of findings – but also the person making the findings.

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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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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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