US-guided percutaneous injection of thrombin is successful and safe in the management of femoral pseudoaneurysms. The increase of thrombin-antithrombin III complex indicates the possibility of thrombin passage into the arterial circulation.

Deep Reinforcement Learning (DRL) has achieved impressive success in many applications. A key component of many DRL models is a neural network representing a Q function, to estimate the expected cumulative reward following a state-action pair. The Q function neural network contains a lot of implicit knowledge about the RL problems, but often remains unexamined and uninterpreted. To our knowledge, this work develops the first mimic learning framework for Q functions in DRL. We introduce Linear Model U-trees (LMUTs) to approximate neural network predictions. An LMUT is learned using a novel on-line algorithm that is well-suited for an active play setting, where the mimic learner observes an ongoing interaction between the neural net and the environment. Empirical evaluation shows that an LMUT mimics a Q function substantially better than five baseline methods. The transparent tree structure of an LMUT facilitates understanding the network's learned knowledge by analyzing feature influence, extracting rules, and highlighting the super-pixels in image inputs.

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A variety of machine learning models have been proposed to assess the performance of players in professional sports. However, they have only a limited ability to model how player performance depends on the game context. This paper proposes a new approach to capturing game context: we apply Deep Reinforcement Learning (DRL) to learn an action-value Q function from 3M play-by-play events in the National Hockey League (NHL). The neural network representation integrates both continuous context signals and game history, using a possession-based LSTM. The learned Q-function is used to value players' actions under different game contexts. To assess a player's overall performance, we introduce a novel Game Impact Metric (GIM) that aggregates the values of the player's actions. Empirical Evaluation shows GIM is consistent throughout a play season, and correlates highly with standard success measures and future salary.

Ultrasound is the most widespread diagnostic procedure in obstructive disease of the arteries supplying the brain. The combined non-invasive information on morphology and function makes duplex ultrasound the procedure of choice in screening and follow-up of carotid artery disease. This review deals with all relevant aspects of color duplex ultrasound of the carotids and the vertebral arteries. After a short introduction into the clinical background, the paper focuses on aspects of examination technique. In the main part of the review the relevant ultrasound findings in carotid artery disease are discussed. The different methods for grading stenoses of the internal carotid artery are explained in detail. Other relevant pathologies, such as vertebral artery disease, dissection and aneurysms, are briefly mentioned. The clinical value of ultrasound in the work-up of carotid and vertebral artery disease is briefly discussed in comparison with other imaging procedures.