Where to next? A dynamic model of user preferences

We consider the problem of predicting users’ preferences on online platforms. We build on recent findings suggesting that users’ preferences change over time, and that helping users expand their horizons is important in ensuring that they stay engaged. Most existing models of user preferences attempt to capture simultaneous preferences: “Users who like A tend to like B as well”. In this paper, we argue that these models fail to anticipate changing preferences. To overcome this issue, we seek to understand the structure that underlies the evolution of user preferences. To this end, we propose the Preference Transition Model (PTM), a dynamic model for user preferences towards classes of items. The model enables the estimation of transition probabilities between classes of items over time, which can be used to estimate how users’ tastes are expected to evolve based on their past history. We test our model’s predictive performance on a number of different prediction tasks on data from three different domains: music streaming, restaurant recommendations and movie recommendations, and find that it outperforms competing approaches. We then focus on a music application, and inspect the structure learned by our model. We find that the PTM uncovers remarkable regularities in users’ preference trajectories over time. We believe that these findings could inform a new generation of dynamic, diversity-enhancing recommender systems

State of the art of immunoassay methods for B-type natriuretic peptides: An update

The aim of this review article is to give an update on the state of the art of the immunoassay methods for the measurement of B-type natriuretic peptide (BNP) and its related peptides. Using chromatographic procedures, several studies reported an increasing number of circulating peptides related to BNP in human plasma of patients with heart failure. These peptides may have reduced or even no biological activity. Furthermore, other studies have suggested that, using immunoassays that are considered specific for BNP, the precursor of the peptide hormone, proBNP, constitutes a major portion of the peptide measured in plasma of patients with heart failure. Because BNP immunoassay methods show large (up to 50%) systematic differences in values, the use of identical decision values for all immunoassay methods, as suggested by the most recent international guidelines, seems unreasonable. Since proBNP significantly cross-reacts with all commercial immunoassay methods considered specific for BNP, manufacturers should test and clearly declare the degree of cross-reactivity of glycosylated and non-glycosylated proBNP in their BNP immunoassay methods. Clinicians should take into account that there are large systematic differences between methods when they compare results from different laboratories that use different BNP immunoassays. On the other hand, clinical laboratories should take part in external quality assessment (EQA) programs to evaluate the bias of their method in comparison to other BNP methods. Finally, the authors believe that the development of more specific methods for the active peptide, BNP1–32, should reduce the systematic differences between methods and result in better harmonization of results

Nonthyroidal illness and the cardiorenal syndrome

Clinical epidemiolog