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https://www.readbyqxmd.com/read/28229132/representing-documents-via-latent-keyphrase-inference
#1
Jialu Liu, Xiang Ren, Jingbo Shang, Taylor Cassidy, Clare R Voss, Jiawei Han
Many text mining approaches adopt bag-of-words or n-grams models to represent documents. Looking beyond just the words, i.e., the explicit surface forms, in a document can improve a computer's understanding of text. Being aware of this, researchers have proposed concept-based models that rely on a human-curated knowledge base to incorporate other related concepts in the document representation. But these methods are not desirable when applied to vertical domains (e.g., literature, enterprise, etc.) due to low coverage of in-domain concepts in the general knowledge base and interference from out-of-domain concepts...
April 2016: Proceedings of the International World-Wide Web Conference
https://www.readbyqxmd.com/read/28227990/using-computational-phantoms-to-improve-delivery-of-tumor-treating-fields-ttfields-to-patients
#2
Ze'ev Bomzon, Hadas Sara Hershkovich, Noa Urman, Aafia Chaudhry, Dario Garcia-Carracedo, Anders R Korshoej, Uri Weinberg, Cornelia Wenger, Pedro Miranda, Yoram Wasserman, Eilon D Kirson, Yoram, Ze'ev Bomzon, Hadas Sara Hershkovich, Noa Urman, Aafia Chaudhry, Dario Garcia-Carracedo, Anders R Korshoej, Uri Weinberg, Cornelia Wenger, Pedro Miranda, Yoram Wasserman, Eilon D Kirson, Yoram, Uri Weinberg, Cornelia Wenger, Noa Urman, Hadas Sara Hershkovich, Yoram Wasserman, Anders R Korshoej, Eilon D Kirson, Dario Garcia-Carracedo, Pedro Miranda, Aafia Chaudhry, Zeev Bomzon, Yoram
This paper reviews the state-of-the-art in simulation-based studies of Tumor Treating Fields (TTFields) and highlights major aspects of TTFields in which simulation-based studies could affect clinical outcomes. A major challenge is how to simulate multiple scenarios rapidly for TTFields delivery. Overcoming this challenge will enable a better understanding of how TTFields distribution is correlated with disease progression, leading to better transducer array designs and field optimization procedures, ultimately improving patient outcomes...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227889/shape-memory-alloy-smart-knee-spacer-to-enhance-knee-functionality-model-design-and-finite-element-analysis
#3
Arvind Gautam, A Bhargavi Rani, Miguel A Callejas, Swati Ghosh Acharyya, Amit Acharyya, Dwaipayan Biswas, Vasundhra Bhandari, Paresh Sharma, Ganesh R Naik, Arvind Gautam, A Bhargavi Rani, Miguel A Callejas, Swati Ghosh Acharyya, Amit Acharyya, Dwaipayan Biswas, Vasundhra Bhandari, Paresh Sharma, Ganesh R Naik, Swati Ghosh Acharyya, Paresh Sharma, Vasundhra Bhandari, A Bhargavi Rani, Arvind Gautam, Dwaipayan Biswas, Miguel A Callejas, Amit Acharyya
In this paper we introduce Shape Memory Alloy (SMA) for designing the tibial part of Total Knee Arthroplasty (TKA) by exploiting the shape-memory and pseudo-elasticity property of the SMA (e.g. NiTi). This would eliminate the drawbacks of the state-of-the art PMMA based knee-spacer including fracture, sustainability, dislocation, tilting, translation and subluxation for tackling the Osteoarthritis especially for the aged people of 45-plus or the athletes. In this paper a Computer Aided Design (CAD) model using SolidWorks for the knee-spacer is presented based on the proposed SMA adopting the state-of-the art industry-standard geometry that is used in the PMMA based spacer design...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227864/automatic-segmentation-of-multimodal-brain-tumor-images-based-on-classification-of-super-voxels
#4
M Kadkhodaei, S Samavi, N Karimi, H Mohaghegh, S M R Soroushmehr, K Ward, A All, K Najarian, M Kadkhodaei, S Samavi, N Karimi, H Mohaghegh, S M R Soroushmehr, K Ward, A All, K Najarian, K Ward, S M R Soroushmehr, A All, S Samavi, M Kadkhodaei, H Mohaghegh, K Najarian, N Karimi
Despite the rapid growth in brain tumor segmentation approaches, there are still many challenges in this field. Automatic segmentation of brain images has a critical role in decreasing the burden of manual labeling and increasing robustness of brain tumor diagnosis. We consider segmentation of glioma tumors, which have a wide variation in size, shape and appearance properties. In this paper images are enhanced and normalized to same scale in a preprocessing step. The enhanced images are then segmented based on their intensities using 3D super-voxels...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227835/multi-chip-dataflow-architecture-for-massive-scale-biophysically-accurate-neuron-simulation
#5
Jaco Hofmann, Amir Zjajo, Carlo Galuzzi, Rene van Leuken, Jaco Hofmann, Amir Zjajo, Carlo Galuzzi, Rene van Leuken, Carlo Galuzzi, Rene Van Leuken, Jaco Hofmann, Amir Zjajo
State-of-the-art neuron simulators are capable of simulating at most few tens/hundreds of neurons in real-time due to the exponential growth in the communication costs with the number of simulated neurons. In this paper, we present a novel, reconfigurable, multi-chip system architecture based on localized communication, which effectively reduces the communication cost to a linear growth. The system is very flexible and it allows to tune, at run-time, various parameters, e.g. the intracellular concentration of chemical compounds, the interconnection scheme between the neurons...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227451/cuff-pressure-induced-pat-changes-modelling-and-experimental-verification-towards-calibration-of-blood-pressure-surrogates
#6
Erik Bresch, Lars Schmitt, Dennis De Matteis, Jens Muehlsteff, Erik Bresch, Lars Schmitt, Dennis De Matteis, Jens Muehlsteff, Erik Bresch, Dennis De Matteis, Lars Schmitt, Jens Muehlsteff
Arterial Blood Pressure (ABP) is one of the most often measured vital parameters in daily clinical practice. State-of-the-Art non-invasive ABP measurement technologies have obvious limitations and are still mainly based on uncomfortable techniques by complete or partial occlusions of arteries. Additionally, embodiments are bulky, difficult to apply for the layman, or provide only intermittent measurements. We have been investigating the pulse arrival time (PAT) and pulse transit time (PTT) methodology for unobtrusive blood pressure (BP) measurements...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227402/simplified-eeg-inverse-solution-for-bci-real-time-implementation
#7
L Duque-Munoz, F Vargas, J D Lopez, L Duque-Munoz, F Vargas, J D Lopez, F Vargas, L Duque-Munoz, J D Lopez
EEG brain imaging has become a promising approach in Brain-computer interface applications. However, accurate reconstruction of active regions and computational burden are still open issues. In this paper, we propose to use a simplified forward model that includes the reduction of the cortical dipoles based on Brodmann areas together with state-of-the-art EEG brain imaging techniques. With this approach the well known Beamformers and Greedy Search inverse solutions become feasible for real-time implementation, while guaranteeing lower localization error than previous approaches used in BCI...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227360/unsupervised-abnormality-detection-using-saliency-and-retinex-based-color-enhancement
#8
Farah Deeba, Shahed K Mohammed, Francis M Bui, Khan A Wahid, Farah Deeba, Shahed K Mohammed, Francis M Bui, Khan A Wahid, Shahed K Mohammed, Francis M Bui, Khan A Wahid, Farah Deeba
An efficient and automated abnormality detection method can significantly reduce the burden of screening of the enormous visual information resulting from capsule endoscopic procedure. As a pre-processing stage, color enhancement could be useful to improve the image quality and the detection performance. Therefore, in this paper, we have proposed a two-stage automated abnormality detection algorithm. In the first stage, an adaptive color enhancement method based on Retinex theory is applied on the endoscopic images...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227312/improving-quality-and-intelligibility-of-speech-using-single-microphone-for-the-broadband-fmri-noise-at-low-snr
#9
Chetan Vahanesa, Chandan K A Reddy, Issa M S Panahi, Chetan Vahanesa, Chandan K A Reddy, Issa M S Panahi, Chetan Vahanesa, Issa M S Panahi, Chandan K A Reddy
Functional Magnetic Resonance Imaging (fMRI) is used in many diagnostic procedures for neurological related disorders. Strong broadband acoustic noise generated during fMRI scan interferes with the speech communication between the physician and the patient. In this paper, we propose a single microphone Speech Enhancement (SE) technique which is based on the supervised machine learning technique and a statistical model based SE technique. The proposed algorithm is robust and computationally efficient and has capability to run in real-time...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227301/an-adapted-double-threshold-protocol-for-spastic-muscles
#10
Pedro M Vieira, Joao F Ferreira, Pedro R Gomes, Carlos S Lima, Pedro M Vieira, Joao F Ferreira, Pedro R Gomes, Carlos S Lima, Pedro M Vieira, Joao F Ferreira, Pedro R Gomes, Carlos S Lima
The onset of muscle contraction has been an important element in the understanding of human motor control system as well as in the development of medical devices. This task is problematic in the study of spasticity using surface Electromyography (sEMG). In fact, spasticity is characterized by involuntary muscle contractions that can be seen as both, a non-stationary background if they are weak or a severe non-stationary EMG signal if they are strong. In other hand, these sEMG signals present a very low signal to noise ratio, beyond the added noise that contaminates this signal...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227270/deep-learning-framework-for-detection-of-hypoglycemic-episodes-in-children-with-type-1-diabetes
#11
Phyo Phyo San, Sai Ho Ling, Hung T Nguyen, Phyo Phyo San, Sai Ho Ling, Hung T Nguyen, Sai Ho Ling, Hung T Nguyen, Phyo Phyo San
Most Type 1 diabetes mellitus (T1DM) patients have hypoglycemia problem. Low blood glucose, also known as hypoglycemia, can be a dangerous and can result in unconsciousness, seizures and even death. In recent studies, heart rate (HR) and correct QT interval (QTc) of the electrocardiogram (ECG) signal are found as the most common physiological parameters to be effected from hypoglycemic reaction. In this paper, a state-of-the-art intelligent technology namely deep belief network (DBN) is developed as an intelligent diagnostics system to recognize the onset of hypoglycemia...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227257/why-should-you-model-time-when-you-use-markov-models-for-heart-sound-analysis
#12
Jorge Oliveira, Theofrastos Mantadelis, Miguel Coimbra, Jorge Oliveira, Theofrastos Mantadelis, Miguel Coimbra, Jorge Oliveira, Miguel Coimbra, Theofrastos Mantadelis
Auscultation is a widely used technique in clinical activity to diagnose heart diseases. However, heart sounds are difficult to interpret because a) of events with very short temporal onset between them (tens of milliseconds) and b) dominant frequencies that are out of the human audible spectrum. In this paper, we propose a model to segment heart sounds using a semi-hidden Markov model instead of a hidden Markov model. Our model in difference from the state-of-the-art hidden Markov models takes in account the temporal constraints that exist in heart cycles...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227213/segmentation-of-optic-disc-and-optic-cup-in-retinal-fundus-images-using-shape-regression
#13
Suman Sedai, Pallab K Roy, Dwarikanath Mahapatra, Rahil Garnavi, Suman Sedai, Pallab K Roy, Dwarikanath Mahapatra, Rahil Garnavi, Suman Sedai, Pallab K Roy, Rahil Garnavi, Dwarikanath Mahapatra
Glaucoma is one of the leading cause of blindness. The manual examination of optic cup and disc is a standard procedure used for detecting glaucoma. This paper presents a fully automatic regression based method which accurately segments optic cup and disc in retinal colour fundus image. First, we roughly segment optic disc using circular hough transform. The approximated optic disc is then used to compute the initial optic disc and cup shapes. We propose a robust and efficient cascaded shape regression method which iteratively learns the final shape of the optic cup and disc from a given initial shape...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227210/retinal-image-registration-through-simultaneous-camera-pose-and-eye-shape-estimation
#14
Carlos Hernandez-Matas, Xenophon Zabulis, Antonis A Argyros, Carlos Hernandez-Matas, Xenophon Zabulis, Antonis A Argyros, Xenophon Zabulis, Antonis A Argyros
In this paper, a retinal image registration method is proposed. The approach utilizes keypoint correspondences and assumes that the human eye has a spherical or ellipsoidal shape. The image registration problem amounts to solving a camera 3D pose estimation problem and, simultaneously, an eye 3D shape estimation problem. The camera pose estimation problem is solved by estimating the relative pose between the views from which the images were acquired. The eye shape estimation problem parameterizes the shape and orientation of an ellipsoidal model for the eye...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227188/conformai-electronics-for-longitudinal-bio-sensing-in-at-home-assistive-and-rehabilitative-devices
#15
John C Batchelor, Stephen G Yeates, Alexander J Casson, John C Batchelor, Stephen G Yeates, Alexander J Casson, Stephen G Yeates, John C Batchelor, Alexander J Casson
Wearable electronics are revolutionizing personalized and preventative healthcare by allowing the easy, unobtrusive, and long term monitoring of a range of body parameters. Conformal electronics which attach directly to the skin in a very robust and long term manner are envisioned as the next generation of highly portable miniaturized computing devices, beyond wearables. In this paper we overview the state-of-the-art in conformal electronics created using silver nanoparticle inkjet printed techniques for home assistive and rehabilitative devices...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227111/sleep-stage-recognition-using-respiration-signal
#16
Jialei Yang, James M Keller, Mihail Popescu, Marjorie Skubic, Jialei Yang, James M Keller, Mihail Popescu, Marjorie Skubic, James M Keller, Mihail Popescu, Marjorie Skubic, Jialei Yang
This paper presents a sleep stage recognition system for Awake, rapid eye movement (REM) and non-REM (NREM) sleep detection. Two respiratory variability (RV) features are extracted from oro-nasal airflow signals provided in the sleep-EDF (Expanded) database. A two layer system with threshold comparison classifier is implemented. This system achieved state-of-the-art performance with simple features and classifiers. The average accuracy of 74.00%±5.30% and Cohen's kappa coefficient of 0.49±0.08 were achieved with 21 recordings...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227017/reconfigurable-hardware-software-codesign-methodology-for-protein-identification
#17
Venkateshwarlu Y Gudur, Sandeep Thallada, Abhinay R Deevi, Venkata Krishna Gande, Amit Acharyya, Vasundhra Bhandari, Paresh Sharma, Saqib Khursheed, Ganesh R Naik, Venkateshwarlu Y Gudur, Sandeep Thallada, Abhinay R Deevi, Venkata Krishna Gande, Amit Acharyya, Vasundhra Bhandari, Paresh Sharma, Saqib Khursheed, Ganesh R Naik, Saqib Khursheed, Paresh Sharma, Vasundhra Bhandari, Venkata Krishna Gande, Venkateshwarlu Y Gudur, Abhinay R Deevi, Amit Acharyya, Sandeep Thallada, Ganesh R Naik
In this paper we propose an on-the-fly reconfigurable hardware-software codesign based reconfigurable solution for real-time protein identification. Reconfigurable string matching is performed in the disciplines of protein identification and biomarkers discovery. With the generation of plethora of sequenced data and number of biomarkers for several diseases, it is becoming necessary to have an accelerated processing and on-the-fly reconfigurable system design methodology to bring flexibility to its usage in the medical science community without the need of changing the entire hardware every time with the advent of new biomarker or protein...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226788/decoding-of-responses-to-mixed-frequency-and-phase-coded-visual-stimuli-using-multiset-canonical-correlation-analysis
#18
Kaori Suefusa, Toshihisa Tanaka, Kaori Suefusa, Toshihisa Tanaka, Toshihisa Tanaka, Kaori Suefusa
Brain-computer interfacing (BCI) based on steady-state visual evoked potentials (SSVEPs) is one of the most practical BCIs because of its high recognition accuracies and little training of a user. Mixed frequency and phase coding which can implement a number of commands and achieve a high information transfer rate (ITR) has recently been gaining much attention. In order to implement mixed-coded SSVEP-BCI as a reliable interface, it is important to detect commands fast and accurately. This paper presents a novel method to recognize mixed-coded SSVEPs which achieves high performance...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226760/a-new-approach-of-oral-cancer-detection-using-bilateral-texture-features-in-digital-infrared-thermal-images
#19
M Chakraborty, S Mukhopadhyay, A Dasgupta, S Patsa, N Anjum, J G Ray, M Chakraborty, S Mukhopadhyay, A Dasgupta, S Patsa, N Anjum, J G Ray, S Patsa, A Dasgupta, N Anjum, M Chakraborty, S Mukhopadhyay, J G Ray
Oral cancer is one of the most prevalent form of cancer and its severity is aggrandized specially among the socio-economically backward population in developing countries. A major fraction of patient population is unable to avail diagnosis for oral cancer due to scarcity of state-of-the-art infrastructure and experienced oral and maxillofacial pathologist. Contemporary gold standard of oral cancer confirmation relies on biopsy report. But biopsy is invasive and thus patients are usually reluctant to undergo this test...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226759/melanoma-detection-by-analysis-of-clinical-images-using-convolutional-neural-network
#20
E Nasr-Esfahani, S Samavi, N Karimi, S M R Soroushmehr, M H Jafari, K Ward, K Najarian, E Nasr-Esfahani, S Samavi, N Karimi, S M R Soroushmehr, M H Jafari, K Ward, K Najarian, M H Jafari, S M R Soroushmehr, E Nasr-Esfahani, S Samavi, K Najarian, N Karimi, K Ward
Melanoma, most threatening type of skin cancer, is on the rise. In this paper an implementation of a deep-learning system on a computer server, equipped with graphic processing unit (GPU), is proposed for detection of melanoma lesions. Clinical (non-dermoscopic) images are used in the proposed system, which could assist a dermatologist in early diagnosis of this type of skin cancer. In the proposed system, input clinical images, which could contain illumination and noise effects, are preprocessed in order to reduce such artifacts...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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