Researchers used large language models to identify diabetic retinopathy and classify its severity from unstructured medical reports.
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People have to be in the loop when machine learning is adapted for medical use.
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The MAITE project studied how artificial intelligence could be used to predict the multidisciplinary service use of the elderly.
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A model locates nerve canals in the lower jaw quickly and precisely, helping radiologists and dentists save time and effort.
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Experts from FCAI and Aalto University on how AI is impacting healthcare services, reliability and mechanics of automated medicine, and why regulation and validation is vital.
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Finnish researchers have developed a new automatized way to localise mandibular canals.
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AI and machine learning methods can help tackle the coronavirus epidemic in many ways.
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Researchers from the University of Helsinki in Finland, Simon Fraser University in Canada and Imperial College London combined genomic data, models of bacterial evolution and machine learning to predict how vaccines could be optimised for specific age groups, geographic regions and communities of bacteria.
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A deep neural network model helps predict healthcare visits by elderly people, with the potential to save millions.
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Finnish AI researchers have developed a deep learning system that shows great potential in detecting diabetic eye diseases, which could facilitate doctors’ work and decrease healthcare expenses.
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