Haoda Fu

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—Multiple types of heterogeneity, such as label het-erogeneity and feature heterogeneity, often co-exist in many real-world data mining applications, such as news article catego-rization, gene functionality prediction. To effectively leverage such heterogeneity, in this paper, we propose a novel graph-based framework for Learning with both Label and Feature(More)
Network meta-analysis (NMA) expands the scope of a conventional pairwise meta-analysis to simultaneously handle multiple treatment comparisons. However, some trials may appear to deviate markedly from the others and thus be inappropriate to be synthesized in the NMA. In addition, the inclusion of these trials in evidence synthesis may lead to bias in(More)
Meta-analysis has become an acceptable and powerful tool for pooling quantitative results from multiple studies addressing the same question. It estimates the effect difference between two treatments when they have been compared head-to-head. However, limitations occur when there are more than two treatments of interest, and some of them have not been(More)
Multiple types of heterogeneity including label heterogeneity and feature heterogeneity often co-exist in many real-world data mining applications, such as diabetes treatment classification, gene functionality prediction, and brain image analysis. To effectively leverage such heterogeneity, in this article, we propose a novel graph-based model for Learning(More)
Availability of individual patient-level data (IPD) broadens the scope of network meta-analysis (NMA) and enables us to incorporate patient-level information. Although IPD is a potential gold mine in biomedical areas, methodological development has been slow owing to limited access to such data. In this paper, we propose a Bayesian IPD NMA modeling(More)
INTRODUCTION American Diabetes Association consensus guidelines emphasize individualized treatment in the management of type 2 diabetes mellitus (T2DM). Early glycemic response is a clinical marker that may predict longer term efficacy for individual patients and provide a clinical tool to enhance personalized treatment. This analysis evaluated whether(More)
I n the July issue of Diabetes, Butler et al. (1) described histopathologic findings of potential concern in pan-creatic tissue obtained at time of death from 8 patients who were reportedly treated with " incretin "-based therapies (sitagliptin or exenatide). A small number of pancreata from diabetes patients and nondiabetic subjects served as controls. We(More)