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https://www.readbyqxmd.com/read/29792917/storage-visualization-and-navigation-of-3d-genomics-data
#1
Jérôme Waldispühl, Eric Zhang, Alexander Butyaev, Elena Nazarova, Yan Cyr
The field of 3D genomics grew at increasing rates in the last decade. The volume and complexity of 2D and 3D data produced is progressively outpacing the capacities of the technology previously used for distributing genome sequences. The emergence of new technologies provides also novel opportunities for the development of innovative approaches. In this paper, we review the state-of-the-art computing technology, as well as the solutions adopted by the platforms currently available.
May 21, 2018: Methods: a Companion to Methods in Enzymology
https://www.readbyqxmd.com/read/29791424/-primary-biliary-cholangitis-part-2-state-of-the-art-diagnosis-associated-diseases-treatment-and-prognosis
#2
Diego Andrés Rodríguez Lugo, Jorge Julián Coronado Tovar, Giovana Alejandra Solano Villamarin, Wiliam Otero Regino
Primary biliary cholangitis (PBC) is a chronic autoimmune cholangiopathy characterized by a selective destruction of biliary epithelial cells of small and medium caliber hepatic ducts, which mainly affects women. The main symptoms are fatigue and pruritus, however, a large proportion of patients may be asymptomatic. The diagnosis is based on AMA titers >1:40, alkaline phosphatase >1.5 times the upper limit for more than 24 weeks and compatible liver histology. It is associated with multiple autoimmune diseases mainly extrahepatic, thyroid diseases, bone diseases, among others...
January 2018: Revista de Gastroenterología del Perú: órgano Oficial de la Sociedad de Gastroenterología del Perú
https://www.readbyqxmd.com/read/29790909/ebic-an-evolutionary-based-parallel-biclustering-algorithm-for-pattern-discovery
#3
Patryk Orzechowski, Moshe Sipper, Xiuzhen Huang, Jason H Moore
Motivation: Biclustering algorithms are commonly used for gene expression data analysis. However, accurate identification of meaningful structures is very challenging and state-of-the-art methods are incapable of discovering with high accuracy different patterns of high biological relevance. Results: In this paper a novel biclustering algorithm based on evolutionary computation, a subfield of artificial intelligence (AI), is introduced. The method called EBIC aims to detect order-preserving patterns in complex data...
May 22, 2018: Bioinformatics
https://www.readbyqxmd.com/read/29789276/novel-method-to-efficiently-create-an-mhealth-app-implementation-of-a-real-time-electrocardiogram-r-peak-detector
#4
Vadim Gliner, Joachim Behar, Yael Yaniv
BACKGROUND: In parallel to the introduction of mobile communication devices with high computational power and internet connectivity, high-quality and low-cost health sensors have also become available. However, although the technology does exist, no clinical mobile system has been developed to monitor the R peaks from electrocardiogram recordings in real time with low false positive and low false negative detection. Implementation of a robust electrocardiogram R peak detector for various arrhythmogenic events has been hampered by the lack of an efficient design that will conserve battery power without reducing algorithm complexity or ease of implementation...
May 22, 2018: JMIR MHealth and UHealth
https://www.readbyqxmd.com/read/29787381/multi-atlas-based-segmentation-should-we-prefer-the-best-atlas-group-over-the-group-of-best-atlases
#5
Paolo Zaffino, Delia Ciardo, Patrik Raudaschl, Karl Fritscher, Rosalinda Ricotti, Daniela Alterio, Giulia Marvaso, Cristiana Fodor, Guido Baroni, Francesco Amato, Roberto Orecchia, Barbara Alicja Jereczek-Fossa, Gregory C Sharp, Maria Francesca Spadea
Multi Atlas Based Segmentation (MABS) uses a database of atlas images, and an atlas selection process is used to choose an atlas subset for registration and voting. In the current state of the art, atlases are chosen according to a similarity criterion between the target subject and each atlas in the database. In this paper, we propose a new concept for atlas selection that relies on selecting the best performing group of atlases rather than the group of highest scoring individual atlases.
 Experiments were performed using CT images of 50 patients, with contours of brainstem and parotid glands...
May 22, 2018: Physics in Medicine and Biology
https://www.readbyqxmd.com/read/29786460/counterexample-driven-genetic-programming-heuristic-program-synthesis-from-formal-specifications
#6
Iwo Błądek, Krzysztof Krawiec, Jerry Swan
Conventional genetic programming (GP) can only guarantee that synthesized programs pass tests given by the provided input-output examples. The alternative to such test-based approach is synthesizing programs by formal specification, typically realized with exact, non-heuristic algorithms. In this paper, we build on our earlier study on Counterexample-Based Genetic Programming (CDGP), an evolutionary heuristic that synthesizes programs from formal specifications. The candidate programs in CDGP undergo formal verification with a Satisfiability Modulo Theory (SMT) solver, which results in counterexamples that are subsequently turned into tests and used to calculate fitness...
May 22, 2018: Evolutionary Computation
https://www.readbyqxmd.com/read/29786181/-new-scenarios-in-secondary-hyperparathyroidism-etelcalcetide-position-paper-of-nephrologists-form-lombardy
#7
Antonio Bellasi, Mario Cozzolino, Fabio Malberti, Giovanni Cancarini, Ciro Esposito, Augusto Genderini, Carlo Maria Guastoni, Patrizia Ondei, Giuseppe Pontoriero, Ugo Teatini, Giuseppe Vezzoli, Piergiorgio Messa, Francesco Locatelli
Bone mineral abnormalities (defined as Chronic Kidney Disease Mineral Bone Disorder; CKD-MBD) are prevalent and associated with a substantial risk burden and poor prognosis in CKD population. Several lines of evidence support the notion that a large proportion of patients receiving maintenance dialysis experience a suboptimal biochemical control of CKD-MBD. Although no study has ever demonstrated conclusively that CKD-MBD control is associated with improved survival, an expanding therapeutic armamentarium is available to correct bone mineral abnormalities...
May 2018: Giornale Italiano di Nefrologia: Organo Ufficiale Della Società Italiana di Nefrologia
https://www.readbyqxmd.com/read/29784939/automatic-cone-photoreceptor-localisation-in-healthy-and-stargardt-afflicted-retinas-using-deep-learning
#8
Benjamin Davidson, Angelos Kalitzeos, Joseph Carroll, Alfredo Dubra, Sebastien Ourselin, Michel Michaelides, Christos Bergeles
We present a robust deep learning framework for the automatic localisation of cone photoreceptor cells in Adaptive Optics Scanning Light Ophthalmoscope (AOSLO) split-detection images. Monitoring cone photoreceptors with AOSLO imaging grants an excellent view into retinal structure and health, provides new perspectives into well known pathologies, and allows clinicians to monitor the effectiveness of experimental treatments. The MultiDimensional Recurrent Neural Network (MDRNN) approach developed in this paper is the first method capable of reliably and automatically identifying cones in both healthy retinas and retinas afflicted with Stargardt disease...
May 21, 2018: Scientific Reports
https://www.readbyqxmd.com/read/29783760/diagnosing-breast-cancer-with-microwave-technology-remaining-challenges-and-potential-solutions-with-machine-learning
#9
Bárbara L Oliveira, Daniela Godinho, Martin O'Halloran, Martin Glavin, Edward Jones, Raquel C Conceição
Currently, breast cancer often requires invasive biopsies for diagnosis, motivating researchers to design and develop non-invasive and automated diagnosis systems. Recent microwave breast imaging studies have shown how backscattered signals carry relevant information about the shape of a tumour, and tumour shape is often used with current imaging modalities to assess malignancy. This paper presents a comprehensive analysis of microwave breast diagnosis systems which use machine learning to learn characteristics of benign and malignant tumours...
May 19, 2018: Diagnostics
https://www.readbyqxmd.com/read/29783686/routing-protocols-for-underwater-wireless-sensor-networks-taxonomy-research-challenges-routing-strategies-and-future-directions
#10
Anwar Khan, Ihsan Ali, Abdullah Ghani, Nawsher Khan, Mohammed Alsaqer, Atiq Ur Rahman, Hasan Mahmood
Recent research in underwater wireless sensor networks (UWSNs) has gained the attention of researchers in academia and industry for a number of applications. They include disaster and earthquake prediction, water quality and environment monitoring, leakage and mine detection, military surveillance and underwater navigation. However, the aquatic medium is associated with a number of limitations and challenges: long multipath delay, high interference and noise, harsh environment, low bandwidth and limited battery life of the sensor nodes...
May 18, 2018: Sensors
https://www.readbyqxmd.com/read/29782993/generalized-recurrent-neural-network-accommodating-dynamic-causal-modeling-for-functional-mri-analysis
#11
Yuan Wang, Yao Wang, Yvonne W Lui
Dynamic Causal Modeling (DCM) is an advanced biophysical model which explicitly describes the entire process from experimental stimuli to functional magnetic resonance imaging (fMRI) signals via neural activity and cerebral hemodynamics. To conduct a DCM study, one needs to represent the experimental stimuli as a compact vector-valued function of time, which is hard in complex tasks such as book reading and natural movie watching. Deep learning provides the state-of-the-art signal representation solution, encoding complex signals into compact dense vectors while preserving the essence of the original signals...
May 18, 2018: NeuroImage
https://www.readbyqxmd.com/read/29778931/monitoring-tool-usage-in-surgery-videos-using-boosted-convolutional-and-recurrent-neural-networks
#12
Hassan Al Hajj, Mathieu Lamard, Pierre-Henri Conze, Béatrice Cochener, Gwenolé Quellec
This paper investigates the automatic monitoring of tool usage during a surgery, with potential applications in report generation, surgical training and real-time decision support. Two surgeries are considered: cataract surgery, the most common surgical procedure, and cholecystectomy, one of the most common digestive surgeries. Tool usage is monitored in videos recorded either through a microscope (cataract surgery) or an endoscope (cholecystectomy). Following state-of-the-art video analysis solutions, each frame of the video is analyzed by convolutional neural networks (CNNs) whose outputs are fed to recurrent neural networks (RNNs) in order to take temporal relationships between events into account...
May 9, 2018: Medical Image Analysis
https://www.readbyqxmd.com/read/29775951/retinal-blood-vessel-segmentation-using-fully-convolutional-network-with-transfer-learning
#13
Zhexin Jiang, Hao Zhang, Yi Wang, Seok-Bum Ko
Since the retinal blood vessel has been acknowledged as an indispensable element in both ophthalmological and cardiovascular disease diagnosis, the accurate segmentation of the retinal vessel tree has become the prerequisite step for automated or computer-aided diagnosis systems. In this paper, a supervised method is presented based on a pre-trained fully convolutional network through transfer learning. This proposed method has simplified the typical retinal vessel segmentation problem from full-size image segmentation to regional vessel element recognition and result merging...
April 26, 2018: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/29771918/a-hybrid-q-learning-sine-cosine-based-strategy-for-addressing-the-combinatorial-test-suite-minimization-problem
#14
Kamal Z Zamli, Fakhrud Din, Bestoun S Ahmed, Miroslav Bures
The sine-cosine algorithm (SCA) is a new population-based meta-heuristic algorithm. In addition to exploiting sine and cosine functions to perform local and global searches (hence the name sine-cosine), the SCA introduces several random and adaptive parameters to facilitate the search process. Although it shows promising results, the search process of the SCA is vulnerable to local minima/maxima due to the adoption of a fixed switch probability and the bounded magnitude of the sine and cosine functions (from -1 to 1)...
2018: PloS One
https://www.readbyqxmd.com/read/29771675/action-driven-visual-object-tracking-with-deep-reinforcement-learning
#15
Sangdoo Yun, Jongwon Choi, Youngjoon Yoo, Kimin Yun, Jin Young Choi
In this paper, we propose an efficient visual tracker, which directly captures a bounding box containing the target object in a video by means of sequential actions learned using deep neural networks. The proposed deep neural network to control tracking actions is pretrained using various training video sequences and fine-tuned during actual tracking for online adaptation to a change of target and background. The pretraining is done by utilizing deep reinforcement learning (RL) as well as supervised learning...
June 2018: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/29771662/optimal-and-autonomous-control-using-reinforcement-learning-a-survey
#16
Bahare Kiumarsi, Kyriakos G Vamvoudakis, Hamidreza Modares, Frank L Lewis
This paper reviews the current state of the art on reinforcement learning (RL)-based feedback control solutions to optimal regulation and tracking of single and multiagent systems. Existing RL solutions to both optimal and control problems, as well as graphical games, will be reviewed. RL methods learn the solution to optimal control and game problems online and using measured data along the system trajectories. We discuss Q-learning and the integral RL algorithm as core algorithms for discrete-time (DT) and continuous-time (CT) systems, respectively...
June 2018: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/29770309/interventional-radiology-of-the-thyroid-gland-critical-review-and-state-of-the-art
#17
REVIEW
Antonio Barile, Simone Quarchioni, Federico Bruno, Anna Maria Ierardi, Francesco Arrigoni, Aldo Victor Giordano, Sergio Carducci, Marco Varrassi, Giampaolo Carrafiello, Ferdinando Caranci, Alessandra Splendiani, Ernesto Di Cesare, Carlo Masciocchi
Thyroid nodules are a common incidental finding during a routinely ultrasound (US) exam unrelated to the thyroid gland in the healthy adult population with a prevalence of 20-76%. As treated before with surgery, in the last years new minimally invasive techniques have been developed as an alternative to surgery. The aim of this review, based on newly revised guidelines, is to provide some information regarding the basic principles, indications, materials, techniques, and results of mini-invasive procedures or treatments for thyroid nodules...
April 2018: Gland Surgery
https://www.readbyqxmd.com/read/29770256/network-inference-via-the-time-varying-graphical-lasso
#18
David Hallac, Youngsuk Park, Stephen Boyd, Jure Leskovec
Many important problems can be modeled as a system of interconnected entities, where each entity is recording time-dependent observations or measurements. In order to spot trends, detect anomalies, and interpret the temporal dynamics of such data, it is essential to understand the relationships between the different entities and how these relationships evolve over time. In this paper, we introduce the time-varying graphical lasso (TVGL) , a method of inferring time-varying networks from raw time series data...
August 2017: KDD: Proceedings
https://www.readbyqxmd.com/read/29766386/cognitive-assessment-in-multiple-sclerosis-an-italian-consensus
#19
Maria Pia Amato, Vincenzo Brescia Morra, Monica Falautano, Angelo Ghezzi, Benedetta Goretti, Francesco Patti, Alice Riccardi, Flavia Mattioli
The aim of this consensus paper was to define the state of the art on cognitive assessment of persons with multiple sclerosis (PwMS), with the purpose of providing recommendations for the Italian centers involved in MS management. While there are no formal guidelines published regarding the assessment of cognitive function in MS, on the basis of an expert opinion meeting, held in Milan (Italy) on July 4, 2016, we report the recommendations of a panel of Italian experts including MS neurologists and neuropsychologists for the assessment and follow-up of cognitive function in adult MS subjects...
May 15, 2018: Neurological Sciences
https://www.readbyqxmd.com/read/29765298/real-time-tracking-of-selective-auditory-attention-from-m-eeg-a-bayesian-filtering-approach
#20
Sina Miran, Sahar Akram, Alireza Sheikhattar, Jonathan Z Simon, Tao Zhang, Behtash Babadi
Humans are able to identify and track a target speaker amid a cacophony of acoustic interference, an ability which is often referred to as the cocktail party phenomenon. Results from several decades of studying this phenomenon have culminated in recent years in various promising attempts to decode the attentional state of a listener in a competing-speaker environment from non-invasive neuroimaging recordings such as magnetoencephalography (MEG) and electroencephalography (EEG). To this end, most existing approaches compute correlation-based measures by either regressing the features of each speech stream to the M/EEG channels (the decoding approach) or vice versa (the encoding approach)...
2018: Frontiers in Neuroscience
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