Machine learning technique helps predict diagnosis in children with acquired demyelination

A new study has highlighted the potential for machine learning classifiers to help predict diagnosis in children at the first episode of demyelination.

Presenting at MSVirtual2020, Dr Beyza Ciftci from the Hospital for Sick Children in Toronto, Canada, noted that machine learning classifiers can be trained to identify associations and links between multiple multimodal input factors and disease classifications.

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