Machine learning

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News • Machine learning assessment

Heart transplantation: AI can provide decision-making support

Matching the right donor heart to the right recipient at the right time is a complex task. At the ISHLT meeting, experts pointed out how AI can provide unbiased decision-support for transplantation…

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Article • Improving quality and efficiency

Preparing for AI in clinical laboratories

Some year in this decade, AI tools will become ubiquitous within clinical laboratories. AI has the potential to increase the accuracy of laboratory testing and improve the quality and efficiency of…

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News • Warfarin, personalised

AI helps dosing anticoagulation meds in heart surgery patients

Warfarin is sometimes prescribed after heart surgery, but getting the dose right requires a personalised approach for each patient. A new AI tool is designed to help with this complex task.

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News • Interpretable machine learning system

AI to detect colorectal cancer from pathology slides

Researchers work on the first prototype that applies AI to colorectal diagnosis. The prototype achieved a diagnostic acuity of 93.44% and a sensitivity of 99.7% in the detection of high-risk lesions.

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News • Medication safety

Should these pills go together? ML model predicts drug interactions

Not all medication can safely be taken together. Using a machine-learning algorithm, researchers predict interactions that could interfere with a drug’s effectiveness.

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News • Machine learning in sample analysis

Lab-trained pathology AI meets real world: ‘mistakes can happen’

AI models are highly capable in analysing tissue samples – as long as conditions are lab-perfect. Add a little contamination, however, and diagnostic accuracy goes out the window, a new study shows.

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Article • Need for diversity in training datasets

Artificial intelligence in healthcare: not always fair

Machine learning and artificial intelligence (AI) are playing an increasingly important role in medicine and healthcare, and not just since ChatGPT. This is especially true in data-intensive specialties such as radiology, pathology or intensive care. The quality of diagnostics and decision-making via AI, however, does not only depend on a sophisticated algorithm but – crucially – on the…

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