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Teaching AI about symmetry could improve prenatal diagnosis

Original: Why teaching AI about symmetry could make prenatal diagnosis more reliable

MIT researchers report that incorporating symmetry principles into AI models could make prenatal diagnosis more reliable. By designing algorithms that recognise symmetric patterns in medical images, the approach aims to reduce errors and inconsistencies in ultrasound-based screening. The work suggests that building physical and anatomical knowledge into machine learning systems may improve their trustworthiness in clinical settings.

Why now: New MIT research on making AI more reliable for prenatal screening has drawn attention from readers interested in medical AI advances.

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