Types of Coincidences in PET

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Introduces probability, statistics, distributions, inference, likelihood, and combinatorics for studying random events and network modeling.

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Explores the principles and applications of PET imaging, covering topics such as tracers, detection, and future perspectives.

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Explores randomness in biology, covering thermal fluctuations, random walks, and data analysis techniques.

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Discusses the bias-variance tradeoff in machine learning, emphasizing the balance between model complexity and prediction accuracy.

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