Urothelial carcinoma masquerading as retroperitoneal fibrosis: A case report.

Retroperitoneal fibrosis, a rare and often idiopathic condition, poses significant diagnostic challenges. While most cases are considered idiopathic or immune-mediated, a small but important proportion are associated with malignant neoplasms, with implications for prognosis and management. The present study describes the case of a 69-year-old man who presented to the emergency department of the Virgen de las Nieves University Hospital (Granada, Spain), with a 2-week history of epigastric pain, vomiting and altered bowel habits.

Adaptive Trend Filtering for ECG Denoising and Delineation.

Standard recordings of electrocardiograhic signals are contaminated by a large variety of noises and interferences, which impair their analysis and the further related diagnosis. In this article, we propose a method, based on compressive sensing techniques, to remove the main noise artifacts and to locate the main features of the pulses in the electrocardiogram (ECG). The motivation is to use trend filtering with a varying proximal parameter, in order to sequentially capture the peaks of the ECG, which have different functional regularities.

Hierarchical Algorithms for Causality Retrieval in Atrial Fibrillation Intracavitary Electrograms.

Multichannel intracavitary electrograms (EGMs) are acquired at the electrophysiology laboratory to guide radio frequency catheter ablation of patients suffering from atrial fibrillation. These EGMs are used by cardiologists to determine candidate areas for ablation (e.g.

Feature Extraction of Galvanic Skin Responses by Nonnegative Sparse Deconvolution.

Wearable sensors are increasingly taking part in daily activities, not only because of the recent society health concern, but also due to their relevance in the medical industry. In this paper, a galvanic skin response (GSR) extraction technique has been developed in order to interpret electrodermal activity (EDA) records, which can be useful both for ambulatory and health applications. The core of the proposed approach is a novel feature extraction scheme that is based on a nonnegative sparse deconvolution of the observed GSR signals.

Estimation of Symmetric Channels for Discrete Cosine Transform Type-I Multicarrier Systems: A Compressed Sensing Approach.

The problem of channel estimation for multicarrier communications is addressed. We focus on systems employing the Discrete Cosine Transform Type-I (DCT1) even at both the transmitter and the receiver, presenting an algorithm which achieves an accurate estimation of symmetric channel filters using only a small number of training symbols. The solution is obtained by using either matrix inversion or compressed sensing algorithms.

Linear latent force models using Gaussian processes.

Purely data-driven approaches for machine learning present difficulties when data are scarce relative to the complexity of the model or when the model is forced to extrapolate. On the other hand, purely mechanistic approaches need to identify and specify all the interactions in the problem at hand (which may not be feasible) and still leave the issue of how to parameterize the system. In this paper, we present a hybrid approach using Gaussian processes and differential equations to combine data-driven modeling with a physical model of the system.