OBJECTIVE Transcutaneous oxygen tension (TcPO2) measures tissue perfusion and is important in the management of peripheral artery disease (PAD). Ankle brachial index (ABI) is used for the diagnosis of PAD and represents a predictor of major adverse cardiovascular events (MACE), even if in diabetes its diagnostic and predictive value seems to be reduced. No study has evaluated TcPO2 as a predict...

We present a method for designing efficient multigenic predictors with few probes and its application to the prediction of the response to preoperative chemotherapy in breast cancer. In this study, each DNA probe was regarded as an elementary predictor of the response to the chemotherapy and the probes which were selected performed a faithful sampling of the training dataset. In a first stage o...

Objective The measurement of follicular output rate (FORT) has been proposed as a good indicator for evaluating follicular response to the exogenous recombinant folliclestimulating hormone (rFSH). This places FORT as a promising qualitative marker for ovarian function. The objective of the study was to determine FORT as a predictor of oocyte competence, embryo quality and clinical pregnancy aft...

Duncan et al. (2007) presented a new methodology for identifying kindergarten readiness factors and quantifying their importance by determining which of children's developing skills measured around kindergarten entrance would predict later reading and math achievement. This article extends Duncan et al.'s work to identify kindergarten readiness factors with 6 longitudinal data sets. Their resul...

We describe a Deep Learning approach to modeling the relevance of a document’s text to a query, applied to biomedical literature. Instead of mapping each document and query to a common semantic space, we compute a variable-length difference vector between the query and document which is then passed through a deep convolution stage followed by a deep regression network to produce the estimated p...

Binary outcomes that depend on an ordinal predictor in a nonmonotonic way are common in medical data analysis. Such patterns can be addressed in terms of cutpoints: for example, one looks for two cutpoints that define an interval in the range of the ordinal predictor for which the probability of a positive outcome is particularly high (or low). A chi-square test may then be performed to compare...

Machine learning is a tool for building models that accurately represent input training data. When undesired biases concerning demographic groups are in the training data, well-trained models will reflect those biases. We present a framework for mitigating such biases by including a variable for the group of interest and simultaneously learning a predictor and an adversary. The input to the net...

The proliferation of information on the Internet has enabled one find any information he/she is looking for. Nevertheless, almost all of these informations are designed for human readers and are not machine readable. Information extraction is a task that addresses the above problem by extracting a piece of information from unstructured formats. This paper proposes a winner-takes-all based multi...

Random walks on bipartite networks have been used extensively to design personalized recommendation methods. While aging has been identified as a key component in the growth of information networks, most research has focused on the networks’ structural properties and neglected the often available time information. Time has been largely ignored both by the investigated recommendation methods as ...

An indirect model is presented, capable of estimating formant trajectories from text only (Text-to-Formants, TTF). The result is a phonetically correct formant trajectory flow of any virtual speech signal, i.e. one that has never been uttered. The focus is on the pattern forms inside the given sound, taking into account the sound environment (up to quinphone), and not on individual formant valu...