Search results for "recurrent"
showing 10 items of 256 documents
Review on Higher-Order Neural Units to Monitor Cardiac Arrhythmia Patterns
2017
An electrocardiogram (ECG) is a non-invasive technique that checks for problems with the electrical activity of a patient’s heart. ECG is economical and extremely versatile. Some of its characteristics make it a very useful tool to detect cardiac pathologies. The ECG records a series of characteristic waves called PQRST; however, the QRS complex analysis enables the detection of a type of arrhythmia in an ECG. Technological developments enable the storage of a large amount of data, from which knowledge extraction is impossible without a powerful data processing tool; in particular, an adequate signal processing tool, whose output provides reliable parameters as a basis to make a precise cli…
Hypothalamic S-Nitrosylation Contributes to the Counter-Regulatory Response Impairment following Recurrent Hypoglycemia
2013
http://www.ncbi.nlm.nih.gov/pubmed/23894333; International audience; AIMS: Hypoglycemia is a severe side effect of intensive insulin therapy. Recurrent hypoglycemia (RH) impairs the counter-regulatory response (CRR) which restores euglycemia. During hypoglycemia, ventromedial hypothalamus (VMH) production of nitric oxide (NO) and activation of its receptor soluble guanylyl cyclase (sGC) are critical for the CRR. Hypoglycemia also increases brain reactive oxygen species (ROS) production. NO production in the presence of ROS causes protein S-nitrosylation. S-nitrosylation of sGC impairs its function and induces desensitization to NO. We hypothesized that during hypoglycemia, the interaction b…
336 Is a vaginectomy enough or is a pelvic exenteration always required for surgical treatment of recurrent cervical cancer?
2020
Introduction No consensus has yet been reached on the best strategy for treatment of cervical cancer local recurrence. Vaginectomy could be a salvage treatment in selected patients. Methods The records of vaginal recurrent cervical cancer patients admitted at Fondazione Policlinico ‘Agostino Gemelli’ IRCCS in Rome from January 2010 to June 2019 were retrospectively analyzed. We reported perioperative and survival outcomes of vaginectomy with respect to a matched series of pelvic exenteration (PE). Results Fifteen women underwent vaginectomy and 30 patients were submitted to PE. No statistical differences were observed between the two groups at baseline characteristics. The vaginectomy proce…
Tertiary cytoreduction in the setting of recurrent ovarian cancer (Review)
2013
Ovarian cancer is the most lethal gynecological malignancy, with aggressive surgical debulking and adjuvant chemotherapy as the main treatment modalities. Optimal debulking during the primary surgery is significantly correlated with prolonged survival. As surgical techniques and chemotherapeutic agents improve, more patients with prolonged survival may face secondary and tertiary recurrences. The role of surgical debulking in secondary cytoreduction (SC) is not clearly defined and is based on retrospective series. The treatment of patients with primary or secondary recurrences generally consists of second-line chemotherapy, but may be performed on medically fit patients in certain circumsta…
On the Computational Complexity of Binary and Analog Symmetric Hopfield Nets
2000
We investigate the computational properties of finite binary- and analog-state discrete-time symmetric Hopfield nets. For binary networks, we obtain a simulation of convergent asymmetric networks by symmetric networks with only a linear increase in network size and computation time. Then we analyze the convergence time of Hopfield nets in terms of the length of their bit representations. Here we construct an analog symmetric network whose convergence time exceeds the convergence time of any binary Hopfield net with the same representation length. Further, we prove that the MIN ENERGY problem for analog Hopfield nets is NP-hard and provide a polynomial time approximation algorithm for this p…
RNN- and LSTM-Based Soft Sensors Transferability for an Industrial Process
2021
The design and application of Soft Sensors (SSs) in the process industry is a growing research field, which needs to mediate problems of model accuracy with data availability and computational complexity. Black-box machine learning (ML) methods are often used as an efficient tool to implement SSs. Many efforts are, however, required to properly select input variables, model class, model order and the needed hyperparameters. The aim of this work was to investigate the possibility to transfer the knowledge acquired in the design of a SS for a given process to a similar one. This has been approached as a transfer learning problem from a source to a target domain. The implementation of a transf…
Information Abstraction from Crises Related Tweets Using Recurrent Neural Network
2016
Social media has become an important open communication medium during crises. The information shared about a crisis in social media is massive, complex, informal and heterogeneous, which makes extracting useful information a difficult task. This paper presents a first step towards an approach for information extraction from large Twitter data. In brief, we propose a Recurrent Neural Network based model for text generation able to produce a unique text capturing the general consensus of a large collection of twitter messages. The generated text is able to capture information about different crises from tens of thousand of tweets summarized only in a 2000 characters text.
CORENup: a combination of convolutional and recurrent deep neural networks for nucleosome positioning identification
2020
Abstract Background Nucleosomes wrap the DNA into the nucleus of the Eukaryote cell and regulate its transcription phase. Several studies indicate that nucleosomes are determined by the combined effects of several factors, including DNA sequence organization. Interestingly, the identification of nucleosomes on a genomic scale has been successfully performed by computational methods using DNA sequence as input data. Results In this work, we propose CORENup, a deep learning model for nucleosome identification. CORENup processes a DNA sequence as input using one-hot representation and combines in a parallel fashion a fully convolutional neural network and a recurrent layer. These two parallel …
Deep Learning Architectures for DNA Sequence Classification
2016
DNA sequence classification is a key task in a generic computational framework for biomedical data analysis, and in recent years several machine learning technique have been adopted to successful accomplish with this task. Anyway, the main difficulty behind the problem remains the feature selection process. Sequences do not have explicit features, and the commonly used representations introduce the main drawback of the high dimensionality. For sure, machine learning method devoted to supervised classification tasks are strongly dependent on the feature extraction step, and in order to build a good representation it is necessary to recognize and measure meaningful details of the items to cla…
Mašīnmācīšanās pielietojums sporta notikumu prognozēšanā
2017
Dažādu notikumu prognozēšana cilvēcei ir vienmēr bijusi aktuāla. Mūsdienās ir attīstījušās tehnoloģijas, lai to būtu iespējams paveikt balstoties uz pagātnes datiem. Darbā tiek apskatīta sporta notikumu prognozēšana, konkrēti futbola maču iznākumi. Tiek apskatītas vairākas mašīnmācīšanās metodes, kas būtu piemērotākās šī uzdevuma veikšanai. Tiek realizēti un optimizēti divi multi-slāņu perceptrona tīkli un viens vairākkārtējā neironu tīkla, konkrēti LSTM algoritms. Ar tiem tiek veikta simulācija izmantojot reālus datus. Vienā no simulācijām tiek sasniegts pozitīvs rezultāts, sezonas laikā algoritms gūst 65% peļņu.