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System based learning

Farzaneh Karimi-Alavijeh, Saeed Jalili, Masoumeh Sadeghi
BACKGROUND: Metabolic syndrome which underlies the increased prevalence of cardiovascular disease and Type 2 diabetes is considered as a group of metabolic abnormalities including central obesity, hypertriglyceridemia, glucose intolerance, hypertension, and dyslipidemia. Recently, artificial intelligence based health-care systems are highly regarded because of its success in diagnosis, prediction, and choice of treatment. This study employs machine learning technics for predict the metabolic syndrome...
May 2016: ARYA Atherosclerosis
Brent C Pottenger, Richard O Davis, Joanne Miller, Lisa Allen, Melinda Sawyer, Peter J Pronovost
OBJECTIVE: To determine whether Comprehensive Unit-based Safety Program (CUSP) teams could be used to enhance patient experience by improving care transitions and discharge processes in a 318-bed community hospital. METHODS: In 2015, CUSP teams produced feasible solutions by participating in a design-thinking initiative, coupled with performance improvement tools involving data analytics and peer-learning communities. Teams completed a 90-day sprint challenge, involving weekly meetings, monthly department leader meetings, and progress trackers...
October 2016: Quality Management in Health Care
Yi Yang, Juan Wen, Liqiang Guo, Xiang Wan, Peifu Du, Ping Feng, Yi Shi, Qing Wan
Emulating neural behaviors at the synaptic level is of great significance for building neuromorphic computational systems and realizing artificial intelligence. Here, oxide-based electric-double-layer (EDL) thin-film transistors were fabricated by using 3-triethoxysilylpropylamine modified graphene oxide (KH550-GO) electrolyte as the gate dielectrics. Resulting from the EDL effect and electrochemical doping between mobile protons and the indium-zinc-oxide channel layer, long-term synaptic plasticity was emulated in our devices...
October 17, 2016: ACS Applied Materials & Interfaces
Akshansh Gupta, Dhirendra Kumar
A brain computer interface (BCI) is a communication system by which a person can send messages or requests for basic necessities without using peripheral nerves and muscles. Response to mental task-based BCI is one of the privileged areas of investigation. Electroencephalography (EEG) signals are used to represent the brain activities in the BCI domain. For any mental task classification model, the performance of the learning model depends on the extraction of features from EEG signal. In literature, wavelet transform and empirical mode decomposition are two popular feature extraction methods used to analyze a signal having non-linear and non-stationary property...
September 3, 2016: Brain Informatics
Iryna Yavorska, Michael Wehr
Cortical inhibitory neurons exhibit remarkable diversity in their morphology, connectivity, and synaptic properties. Here, we review the function of somatostatin-expressing (SOM) inhibitory interneurons, focusing largely on sensory cortex. SOM neurons also comprise a number of subpopulations that can be distinguished by their morphology, input and output connectivity, laminar location, firing properties, and expression of molecular markers. Several of these classes of SOM neurons show unique dynamics and characteristics, such as facilitating synapses, specific axonal projections, intralaminar input, and top-down modulation, which suggest possible computational roles...
2016: Frontiers in Neural Circuits
Amanda C Sharko, Jim R Fadel, Kris F Kaigler, Marlene A Wilson
Identifying the neurobiological mechanisms that underlie differential sensitivity to stress is critical for understanding the development and expression of stress-induced disorders, such as post-traumatic stress disorder (PTSD). Preclinical studies have suggested that rodents display different phenotypes associated with extinction of Pavlovian conditioned fear responses, with some rodent populations being resistant to extinction. An emerging literature also suggests a role for orexins in the consolidation processes associated with fear learning and extinction...
October 13, 2016: Physiology & Behavior
David Bouget, Max Allan, Danail Stoyanov, Pierre Jannin
In recent years, tremendous progress has been made in surgical practice for example with Minimally Invasive Surgery (MIS). To overcome challenges coming from deported eye-to-hand manipulation, robotic and computer-assisted systems have been developed. Having real-time knowledge of the pose of surgical tools with respect to the surgical camera and underlying anatomy is a key ingredient for such systems. In this paper, we present a review of the literature dealing with vision-based and marker-less surgical tool detection...
September 13, 2016: Medical Image Analysis
Alvin Rajkomar, Joanne Wing Lan Yim, Kevin Grumbach, Ami Parekh
BACKGROUND: Characterizing patient complexity using granular electronic health record (EHR) data regularly available to health systems is necessary to optimize primary care processes at scale. OBJECTIVE: To characterize the utilization patterns of primary care patients and create weighted panel sizes for providers based on work required to care for patients with different patterns. METHODS: We used EHR data over a 2-year period from patients empaneled to primary care clinicians in a single academic health system, including their in-person encounter history and virtual encounters such as telephonic visits, electronic messaging, and care coordination with specialists...
October 14, 2016: JMIR Medical Informatics
John Y-K Lee, Jayesh P Thawani, John Pierce, Ryan Zeh, Maria Martinez-Lage, Michelle Chanin, Ollin Venegas, Sarah Nims, Kim Learned, Jane Keating, Sunil Singhal
BACKGROUND: Although real-time localization of gliomas has improved with intraoperative image guidance systems, these tools are limited by brain shift, surgical cavity deformation, and expense. OBJECTIVE: To propose a novel method to perform near-infrared (NIR) imaging during glioma resections based on preclinical and clinical investigations, in order to localize tumors and to potentially identify residual disease. METHODS: Fifteen patients were identified and administered a Food and Drug Administration-approved, NIR contrast agent (Second Window indocyanine green [ICG], 5 mg/kg) before surgical resection...
October 11, 2016: Neurosurgery
Fabricio Ferreira de Oliveira, Sheilla de Medeiros Correia Marin, Paulo Henrique Ferreira Bertolucci
BACKGROUND: More than 95% of right-handed individuals, as well as almost 80% of left-handed individuals, have left hemisphere dominance for language. The perisylvian networks of the dominant hemisphere tend to be the most important language systems in human brains, usually connected by bidirectional fibres originated from the superior longitudinal fascicle/arcuate fascicle system and potentially modifiable by learning. Neuroplasticity mechanisms take place to preserve neural functions after brain injuries...
October 14, 2016: Brain Injury: [BI]
Lei Zhang, David Zhang
Conventional extreme learning machines (ELMs) solve a Moore-Penrose generalized inverse of hidden layer activated matrix and analytically determine the output weights to achieve generalized performance, by assuming the same loss from different types of misclassification. The assumption may not hold in cost-sensitive recognition tasks, such as face recognition-based access control system, where misclassifying a stranger as a family member may result in more serious disaster than misclassifying a family member as a stranger...
October 11, 2016: IEEE Transactions on Neural Networks and Learning Systems
Bin Hu, Xiaowei Li, Shuting Sun, Martyn Ratcliffe
The research detailed in this paper focuses on the processing of Electroencephalography (EEG) data to identify attention during the learning process. The identification of affect using our procedures is integrated into a simulated distance learning system that provides feedback to the user with respect to attention and concentration. The authors propose a classification procedure that combines correlation-based feature selection (CFS) and a k-nearest-neighbor (KNN) data mining algorithm. To evaluate the CFS+KNN algorithm, it was test against CFS+C4...
October 11, 2016: IEEE/ACM Transactions on Computational Biology and Bioinformatics
N Ramaiah, Ajay Kumar
Iris recognition systems are increasingly deployed for large-scale applications such as national ID programs which continue to acquire millions of iris images to establish identity among billions. However with the availability of variety of iris sensors that are deployed for the iris imaging under different illumination/environment, significant performance degradation is expected while matching such iris images acquired under two different domains (either sensor-specific or wavelength-specific). This paper develops a domain adaptation framework to address this problem and introduces a new algorithm using Markov random fields (MRF) model to significantly improve cross-domain iris recognition...
October 10, 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Norio Iizuka, Koichiro Usuku, Hajime Nakae, Makoto Segawa, Yue Wang, Kahori Ogashiwa, Yusuke Fujita, Hiroyuki Ogihara, Susumu Tazuma, Yoshihiko Hamamoto
Measuring the learning effectiveness of Kampo Medicine (KM) education is challenging. The aim of this study was to develop a web-based test to measure the learning effectiveness of KM education among medical students (MSs). We used an open-source Moodle platform to test 30 multiple-choice questions classified into 8-type fields (eight basic concepts of KM) including "qi-blood-fluid" and "five-element" theories, on 117 fourth-year MSs. The mean (±standard deviation [SD]) score on the web-based test was 30.2 ± 11...
2016: Evidence-based Complementary and Alternative Medicine: ECAM
Gregory P Marchildon
Regionalization is arguably the most significant health reform in Canada since medicare. Although a majority of provinces continue to have regionalized systems in Canada, the policy is more contested today than it was a decade ago. Since Ontario's implementation of local health integration networks (LHINs) in 2006 and Alberta's elimination of regional health authorities (RHAs) in favour of Alberta Health Services in 2008, Canada has had differing approaches to regionalization. However, due to the centralization of physician budgets in provincial health ministries, primary care has not been integrated into any regionalization model in Canada...
2016: HealthcarePapers
Ali Jassem Buabbas, Hamza Mohammad Hassan Al-Shawaf, Abdullah Abdulaziz Almajran
BACKGROUND: In medical education, information and communication technology (ICT) knowledge and skills have become a necessity and an integral part of preparing tomorrow's doctors to be sufficiently competent to use informatics resources effectively and efficiently for the best practice of medicine. OBJECTIVE: This research aimed to study the literacy of the preprofessional students in ICT before and after taking the basic informatics course at the Health Sciences Center at Kuwait University, to understand their potential and their attitudes toward using ICT, including e-learning...
June 20, 2016: JMIR Med Educ
Nadine Tix, Paul Gießler, Ursula Ohnesorge-Radtke, Cord Spreckelsen
BACKGROUND: The Semantically Annotated Media (SAM) project aims to provide a flexible platform for searching, browsing, and indexing medical learning objects (MLOs) based on a semantic network derived from established classification systems. Primarily, SAM supports the Aachen emedia skills lab, but SAM is ready for indexing distributed content and the Simple Knowledge Organizing System standard provides a means for easily upgrading or even exchanging SAM's semantic network. There is a lack of research addressing the usability of MLO indexes or search portals like SAM and the user behavior with such platforms...
November 11, 2015: JMIR Med Educ
Cameron L Randall, John R Shaffer, Daniel W McNeil, Richard J Crout, Robert J Weyant, Mary L Marazita
OBJECTIVES: Dental fear is a prevalent problem that impacts dental treatment-seeking behavior and thus oral, systemic, and psychological health. Among other important predictors, fear of pain has been shown to be a critical component of dental fear. While learning history (id est, past experience) is known to shape development and maintenance of dental fear and fear of pain, minimal work has addressed genetic etiological variables for these healthcare-related anxieties. With the aim of coming to a more complete conceptualization of dental fear, this study assessed the heritability of dental fear and fear of pain and elucidated the role of genetics in the relation between the constructs...
October 11, 2016: Community Dentistry and Oral Epidemiology
Wen-Wai Yim, Sharon W Kwan, Meliha Yetisgen
BACKGROUND: Anaphoric references occur ubiquitously in clinical narrative text. However, the problem, still very much an open challenge, is typically less aggressively focused on in clinical text domain applications. Furthermore, existing research on reference resolution is often conducted disjointly from real-world motivating tasks. OBJECTIVE: In this paper, we present our machine-learning system that automatically performs reference resolution and a rule-based system to extract tumor characteristics, with component-based and end-to-end evaluations...
October 8, 2016: Journal of Biomedical Informatics
Vishal Kumar, Mehak Baweja, Puneet K Singh, Pratyoosh Shukla
Microorganisms play a crucial role in the sustainability of the various ecosystems. The characterization of various interactions between microorganisms and other biotic factors is a necessary footstep to understand the association and functions of microbial communities. Among the different microbial interactions in an ecosystem, plant-microbe interaction plays an important role to balance the ecosystem. The present review explores plant-microbe interactions using gene editing and system biology tools toward the comprehension in improvement of plant traits...
2016: Frontiers in Plant Science
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