Carole Philippe

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OPTISAS is a visualization method that allows describing very precisely a patient with Sleep Apnea Syndrome. Using the events scored by the physician, our method gives a set of graphs that are a detailed representation of the condition, sleep stage and position, in which the events occur. This helps for the diagnosis. This is possible thanks to the(More)
The Sleep Apnea Syndrome is a sleep disorder characterized by frequently repeated respiratory disorders during sleep. It needs the simultaneous recording of many physiological parameters to be diagnosed. The analysis of these curves is a time consuming task made by sleep Physicians. First, they detect some physiological events on each curve and then, they(More)
—Sleep stage identification is the first step in modern sleep disorder diagnostics process. K-complex is an indicator for the sleep stage 2. However, due to the ambiguity of the translation of the medical standards into a computer-based procedure, reliability of automated K-complex detection from the EEG wave is still far from expectation. More(More)
A neurohypophyseal granular cell tumor was found in a 60-year-old man who presented diminished visual acuity. Neuronavigation resection via a fronto-pteronial approach removed split up material. The diagnosis was established by histology and immunochemical studies. Granulous cell tumors, which are common, are rarely located in the neurohypophysis. Their(More)
The preliminary results of the SERVE-HF study have led to the release of safety information with subsequent contraindication to the use of adaptive servo-ventilation (ASV) for the treatment of central sleep apnoeas in patients with chronic symptomatic systolic heart failure with left ventricular ejection fraction (LVEF) ≤ 45%. The aim of this article is to(More)
Scoring sleep stages can be considered as a classification problem. Once the whole recording segmented into 30-seconds epochs, features, extracted from raw signals, are typically injected into machine learning algorithms in order to build a model able to assign a sleep stage, trying to mimic what experts have done on the training set. Such approaches ignore(More)
This paper presents a novel system for automatic sleep staging based on evolutionary technique and symbolic intelligence. Proposed system mimics decision making process of clinical sleep staging using Symbolic Fusion and considers personal singularity with an adaptive thresholds setting up system using Evolutionary Algorithm. It proved to be an effective(More)
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