Read by QxMD icon Read

Learning efficiency

Lindsay Bonsignore, Nicholas Bloom, Karen Steinhauser, Reginald Nichols, Todd Allen, Martha Twaddle, Janet Bull
CONTEXT: The impact of telehealth and remote patient monitoring have not been well established in palliative care populations in rural communities. OBJECTIVES: The objective of this study was to 1) Describe a telehealth palliative care program using the TapCloud remote patient monitoring application and videoconferencing, 2) Evaluate the feasibility, usability, and acceptability of a telehealth system in palliative care, and 3) Use a quality data assessment collection tool (QDACT) in addition to TapCloud ratings of symptom burden and hospice transitions...
March 15, 2018: Journal of Pain and Symptom Management
Jonathan R Kusins, Jason A Strelzow, Marie-Eve LeBel, Louis M Ferreira
PURPOSE: Glenoid reaming is a technically challenging step during shoulder arthroplasty that could possibly be learned during simulation training. Creation of a realistic simulation using vibration feedback in this context is innovative. Our study focused on the development and internal validation of a novel glenoid reaming simulator for potential use as a training tool. METHODS: Vibration and force profiles associated with glenoid reaming were quantified during a cadaveric experiment...
March 17, 2018: International Journal of Computer Assisted Radiology and Surgery
Nils Gessert, Matthias Schl├╝ter, Alexander Schlaefer
Tracking the pose of instruments is a central problem in image-guided surgery. For microscopic scenarios, optical coherence tomography (OCT) is increasingly used as an imaging modality. OCT is suitable for accurate pose estimation due to its micrometer range resolution and volumetric field of view. However, OCT image processing is challenging due to speckle noise and reflection artifacts in addition to the images' 3D nature. We address pose estimation from OCT volume data with a new deep learning-based tracking framework...
March 10, 2018: Medical Image Analysis
Sima Chalavi, Lisa Pauwels, Kirstin-Friederike Heise, Hamed Zivariadab, Celine Maes, Nicolaas A J Puts, Richard A E Edden, Stephan P Swinnen
Efficient practice organization maximizes learning outcome. Although randomization of practice as compared to blocked practice damages training performance, it boosts retention performance, an effect called contextual interference. Motor learning modulates the GABAergic (gamma-aminobutyric acid) system within the sensorimotor cortex (SM); however, it is unclear whether different practice regimes differentially modulate this system and whether this is impacted by aging. Young and older participants were trained on 3 variations of a visuomotor task over 3 days, following either blocked or random practice schedule and retested 6 days later...
February 19, 2018: Neurobiology of Aging
Patrick McAllister, Huiru Zheng, Raymond Bond, Anne Moorhead
Obesity is increasing worldwide and can cause many chronic conditions such as type-2 diabetes, heart disease, sleep apnea, and some cancers. Monitoring dietary intake through food logging is a key method to maintain a healthy lifestyle to prevent and manage obesity. Computer vision methods have been applied to food logging to automate image classification for monitoring dietary intake. In this work we applied pretrained ResNet-152 and GoogleNet convolutional neural networks (CNNs), initially trained using ImageNet Large Scale Visual Recognition Challenge (ILSVRC) dataset with MatConvNet package, to extract features from food image datasets; Food 5K, Food-11, RawFooT-DB, and Food-101...
February 17, 2018: Computers in Biology and Medicine
Ming Xiao, Daozhi Shen, Kevin P Musselman, Walter W Duley, Y Norman Zhou
Neuromorphic computational systems that emulate biological synapses in the human brain are fundamental in the development of artificial intelligence protocols beyond the standard von Neumann architecture. Such systems require new types of building blocks, such as memristors that access a quasi-continuous and wide range of conductive states, which is still an obstacle for the realization of high-efficiency and large-capacity learning in neuromorphoric simulation. Here, we introduce hydrogen and sodium titanate nanobelts, the intermediate products of hydrothermal synthesis of TiO2 nanobelts, to emulate the synaptic behavior...
March 16, 2018: Nanoscale
William J McIlvane, Joanne B Kledaras, Christophe J Gerard, Lorin Wilde, David Smelson
A few noteworthy exceptions notwithstanding, quantitative analyses of relational learning are most often simple descriptive measures of study outcomes. For example, studies of stimulus equivalence have made much progress using measures such as percentage consistent with equivalence relations, discrimination ratio, and response latency. Although procedures may have ad hoc variations, they remain fairly similar across studies. Comparison studies of training variables that lead to different outcomes are few. Yet to be developed are tools designed specifically for dynamic and/or parametric analyses of relational learning processes...
March 12, 2018: Behavioural Processes
Shuchao Pang, Mehmet A Orgun, Zhezhou Yu
BACKGROUND AND OBJECTIVES: The traditional biomedical image retrieval methods as well as content-based image retrieval (CBIR) methods originally designed for non-biomedical images either only consider using pixel and low-level features to describe an image or use deep features to describe images but still leave a lot of room for improving both accuracy and efficiency. In this work, we propose a new approach, which exploits deep learning technology to extract the high-level and compact features from biomedical images...
May 2018: Computer Methods and Programs in Biomedicine
Che-Wei Lin, Elizabeth H Chang, Daniel L Clinciu, Yun-Ting Peng, Wen-Chen Huang, Chien-Chih Wu, Jen-Chieh Wu, Yu-Chuan Li
BACKGROUND AND OBJECTIVE: Objective Structured Clinical Examination (OSCE) has been used in many areas of healthcare training over the years. However, it constantly needs to be upgraded and enhanced due to technological and teaching changes. We aim at implementing an integrative OSCE method which employs informatics via the virtual patient within the pharmacy education curriculum at Taipei Medical University to enhance the pharmacy students' competence for using and disseminating information and to also improve critical thinking and clinical reasoning...
May 2018: Computer Methods and Programs in Biomedicine
C-A Philip, G Dubernard
Endometriosis is difficult to diagnose clinically. Transvaginal sonography (TVS) is a procedure that is known to be operator-dependent, which mean that published evidences has to be balanced with the level of the sonographer that produced the data. The objective of this publication was to assess the performances of the sonography in the diagnosis of endometriosis in order to establish the French national recommendations. We searched the MEDLINE database for publication from January 2000 to September 2017 using keywords associated with endometriosis and sonography...
March 12, 2018: Gynecologie, Obstetrique, Fertilite & Senologie
Hythem Sidky, Jonathan K Whitmer
Existing adaptive bias techniques, which seek to estimate free energies and physical properties from molecular simulations, are limited by their reliance on fixed kernels or basis sets which hinder their ability to efficiently conform to varied free energy landscapes. Further, user-specified parameters are in general non-intuitive yet significantly affect the convergence rate and accuracy of the free energy estimate. Here we propose a novel method, wherein artificial neural networks (ANNs) are used to develop an adaptive biasing potential which learns free energy landscapes...
March 14, 2018: Journal of Chemical Physics
Ryan B Scott, Jason Samaha, Ron Chrisley, Zoltan Dienes
While theories of consciousness differ substantially, the 'conscious access hypothesis', which aligns consciousness with the global accessibility of information across cortical regions, is present in many of the prevailing frameworks. This account holds that consciousness is necessary to integrate information arising from independent functions such as the specialist processing required by different senses. We directly tested this account by evaluating the potential for associative learning between novel pairs of subliminal stimuli presented in different sensory modalities...
March 12, 2018: Cognition
Han Liu, Xianchao Zhang, Xiaotong Zhang
Possible world has shown to be effective for handling various types of data uncertainty in uncertain data management. However, few uncertain data clustering and classification algorithms are proposed based on possible world. Moreover, existing possible world based algorithms suffer from the following issues: (1) they deal with each possible world independently and ignore the consistency principle across different possible worlds; (2) they require the extra post-processing procedure to obtain the final result, which causes that the effectiveness highly relies on the post-processing method and the efficiency is also not very good...
February 27, 2018: Neural Networks: the Official Journal of the International Neural Network Society
Caio M Moreira, Max Rollwage, Kristin Kaduk, Melanie Wilke, Igor Kagan
Humans and other animals constantly evaluate their decisions in order to learn and behave adaptively. Experimentally, such evaluation processes are accessed using metacognitive reports made after decisions, typically using verbally formulated confidence scales. When subjects report high confidence, it reflects a high certainty of being correct, but a low confidence might signify either low certainty about the outcome, or a high certainty of being incorrect. Hence, metacognitive reports might reflect not only different levels of decision certainty, but also two certainty directions (certainty of being correct and certainty of being incorrect)...
March 12, 2018: Cognition
Akihiro Suzuki, Takashi Morie, Hakaru Tamukoh
This paper proposes a shared synapse architecture for autoencoders (AEs), and implements an AE with the proposed architecture as a digital circuit on a field-programmable gate array (FPGA). In the proposed architecture, the values of the synapse weights are shared between the synapses of an input and a hidden layer, and between the synapses of a hidden and an output layer. This architecture utilizes less of the limited resources of an FPGA than an architecture which does not share the synapse weights, and reduces the amount of synapse modules used by half...
2018: PloS One
Kenzie A Cameron, Elaine R Cohen, Joelle R Hertz, Diane B Wayne, Debi Mitra, Jeffrey H Barsuk
OBJECTIVES: The aims of the study were to identify perceived barriers and facilitators to central venous catheter (CVC) insertion among healthcare providers and to understand the extent to which an existing Simulation-Based Mastery Learning (SBML) program may address barriers and leverage facilitators. METHODS: Providers participating in a CVC insertion SBML train-the-trainer program, in addition to intensive care unit nurse managers, were purposively sampled from Veterans Administration Medical Centers located in geographically diverse areas...
March 14, 2018: Journal of Patient Safety
Dieter Galea, Ivan Laponogov, Kirill Veselkov
Motivation: Recognition of biomedical entities from scientific text is a critical component of natural language processing and automated information extraction platforms. Modern named entity recognition approaches rely heavily on supervised machine learning techniques, which are critically dependent on annotated training corpora. These approaches have been shown to perform well when trained and tested on the same source. However, in such scenario, the performance and evaluation of these models may be optimistic, as such models may not necessarily generalize to independent corpora, resulting in potential non-optimal entity recognition for large-scale tagging of widely diverse articles in databases such as PubMed...
March 10, 2018: Bioinformatics
Ilia Korvigo, Andrey Afanasyev, Nikolay Romashchenko, Mikhail Skoblov
Many automatic classifiers were introduced to aid inference of phenotypical effects of uncategorised nsSNVs (nonsynonymous Single Nucleotide Variations) in theoretical and medical applications. Lately, several meta-estimators have been proposed that combine different predictors, such as PolyPhen and SIFT, to integrate more information in a single score. Although many advances have been made in feature design and machine learning algorithms used, the shortage of high-quality reference data along with the bias towards intensively studied in vitro models call for improved generalisation ability in order to further increase classification accuracy and handle records with insufficient data...
2018: PloS One
Maurizio Giordano, Kumar Parijat Tripathi, Mario Rosario Guarracino
BACKGROUND: System toxicology aims at understanding the mechanisms used by biological systems to respond to toxicants. Such understanding can be leveraged to assess the risk of chemicals, drugs, and consumer products in living organisms. In system toxicology, machine learning techniques and methodologies are applied to develop prediction models for classification of toxicant exposure of biological systems. Gene expression data (RNA/DNA microarray) are often used to develop such prediction models...
March 8, 2018: BMC Bioinformatics
Zhizhou Deng, Bharath Chandrasekaran, Suiping Wang, Patrick C M Wong
In second language acquisition studies, the high talker variability training approach has been frequently used to train participants to learn new speech patterns. However, the neuroplasticity induced by training is poorly understood. In the present study, native English speakers were trained on non-native pitch patterns (linguistic tones from Mandarin Chinese) in multi-talker (N = 16) or single-talker (N = 16) training conditions. We focused on two aspects of multi-talker training, voice processing and lexical phonology accessing, and used functional magnetic resonance imaging (fMRI) to measure brain activation and functional connectivity (FC) of two regions of interest in a tone identification task conducted before and after training, namely the anterior part of the right superior temporal gyrus (aRSTG) and the posterior left superior temporal gyrus (pLSTG)...
March 10, 2018: Neurobiology of Learning and Memory
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"