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Explores the application of machine learning in medicine, emphasizing interpretability, variability between patients, and the quest for transparent equations in medical models.
Summarizes Kohonen maps, covering initialization, sampling, similarity-matching, examples, and applications in machine learning and data classification.
Explores individual differences in learning manual control of dynamic balancing in a spaceflight analog task, highlighting the impact of different strategies on performance.