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https://www.readbyqxmd.com/read/29793060/a-computational-framework-for-the-detection-of-subcortical-brain-dysmaturation-in-neonatal-mri-using-3d-convolutional-neural-networks
#1
Rafael Ceschin, Alexandria Zahner, William Reynolds, Jenna Gaesser, Giulio Zuccoli, Cecilia W Lo, Vanathi Gopalakrishnan, Ashok Panigrahy
Deep neural networks are increasingly being used in both supervised learning for classification tasks and unsupervised learning to derive complex patterns from the input data. However, the successful implementation of deep neural networks using neuroimaging datasets requires adequate sample size for training and well-defined signal intensity based structural differentiation. There is a lack of effective automated diagnostic tools for the reliable detection of brain dysmaturation in the neonatal period, related to small sample size and complex undifferentiated brain structures, despite both translational research and clinical importance...
May 21, 2018: NeuroImage
https://www.readbyqxmd.com/read/29792944/enrichment-of-low-density-symbiont-dna-from-minute-insects
#2
Corinne M Stouthamer, Suzanne Kelly, Martha S Hunter
Symbioses between bacteria and insects are often associated with changes in important biological traits that can significantly affect host fitness. To a large extent, studies of these interactions have been based on physiological changes or induced phenotypes in the host, and the genetic mechanisms by which symbionts interact with their hosts have only recently become better understood. Learning about symbionts has been challenging in part due to difficulties such as obtaining enough high quality genomic material for high throughput sequencing technology, especially for symbionts present in low titers, and in small or difficult to rear non-model hosts...
May 21, 2018: Journal of Microbiological Methods
https://www.readbyqxmd.com/read/29792786/imageless-navigation-total-hip-arthroplasty-an-evaluation-of-operative-time
#3
Epaminondas Markos Valsamis, David Ricketts, Adnan Hussain, Amir-Reza Jenabzadeh
INTRODUCTION: Imageless navigation has been successfully integrated in knee arthroplasty but its effectiveness in total hip arthroplasty (THA) has been debated. It has consistently been shown that navigation adds significant time and cost to the operation. Further, the relative success of traditional hip replacements has impeded the adoption of new techniques. METHODS: We compared the operative time between fifty total hip replacements with and without the use of imageless navigation by a single senior surgeon in a retrospective study...
2018: SICOT-J
https://www.readbyqxmd.com/read/29792543/restructuring-saudi-board-in-restorative-dentistry-sbrd-curriculum-using-canmeds-competency
#4
Bahiah Abdulaziz Al Askar, Fahad Saleh Al Sweleh, Ebtesam Ibrahim Al Wasill, Zubair Amin
OBJECTIVE: The purpose of this paper is to describe the process of adopting the Canadian Medical Education Directions for Specialists (CanMEDS) 2015 competency framework in a dental specialty program to reconstruct the Saudi Board in Restorative Dentistry (SBRD) curriculum and disseminate the lessons learned. Method and development process: The process of curriculum development was started with the selection of SBRD curriculum committee and review of CanMEDS framework. The Committee conducted needs assessment among the stakeholders and adopted CanMEDS 2015 competencies through a careful process...
May 24, 2018: Medical Teacher
https://www.readbyqxmd.com/read/29792208/automated-chest-screening-based-on-a-hybrid-model-of-transfer-learning-and-convolutional-sparse-denoising-autoencoder
#5
Changmiao Wang, Ahmed Elazab, Fucang Jia, Jianhuang Wu, Qingmao Hu
OBJECTIVE: In this paper, we aim to investigate the effect of computer-aided triage system, which is implemented for the health checkup of lung lesions involving tens of thousands of chest X-rays (CXRs) that are required for diagnosis. Therefore, high accuracy of diagnosis by an automated system can reduce the radiologist's workload on scrutinizing the medical images. METHOD: We present a deep learning model in order to efficiently detect abnormal levels or identify normal levels during mass chest screening so as to obtain the probability confidence of the CXRs...
May 23, 2018: Biomedical Engineering Online
https://www.readbyqxmd.com/read/29792141/molecular-docking-for-prediction-and-interpretation-of-adverse-drug-reactions
#6
Heng Luo, Achille Fokoue-Nkoutche, Nalini Singh, Lun Yang, Jianying Hu, Ping Zhang
Adverse drug reactions (ADRs) present a major burden for patients and the healthcare industry. Various computational methods have been developed to predict ADRs for drug molecules. However, many of these methods require experimental or surveillance data and cannot be used when only structural information is available. We collected 1,231 small molecule drugs and 600 human proteins and utilized molecular docking to generate binding features among them. We developed machine learning models that use these docking features to make predictions for 1,533 ADRs...
May 23, 2018: Combinatorial Chemistry & High Throughput Screening
https://www.readbyqxmd.com/read/29792074/lessons-learned-conducting-a-multi-center-trial-with-a-military-population-the-tinnitus-retraining-therapy-trial
#7
Roberta W Scherer, Leonora D Sensinger, Benigno Sierra-Irizarry, Craig Formby
Background The Tinnitus Retraining Therapy Trial (TRTT), a randomized, placebo-controlled, multi-center trial, evaluated the efficacy of tinnitus retraining therapy and its individual components, tinnitus-specific educational counseling and sound therapy versus the standard of care, in military practice to improve study participants' quality of life. The trial was conducted at six US military hospitals to take advantage of the greater prevalence of tinnitus in the military population. Methods During the trial, various challenges arose that were uniquely related to the military setting...
May 1, 2018: Clinical Trials: Journal of the Society for Clinical Trials
https://www.readbyqxmd.com/read/29792067/application-of-machine-learning-to-predict-dietary-lapses-during-weight-loss
#8
Stephanie P Goldstein, Fengqing Zhang, John G Thomas, Meghan L Butryn, James D Herbert, Evan M Forman
BACKGROUND: Individuals who adhere to dietary guidelines provided during weight loss interventions tend to be more successful with weight control. Any deviation from dietary guidelines can be referred to as a "lapse." There is a growing body of research showing that lapses are predictable using a variety of physiological, environmental, and psychological indicators. With recent technological advancements, it may be possible to assess these triggers and predict dietary lapses in real time...
May 1, 2018: Journal of Diabetes Science and Technology
https://www.readbyqxmd.com/read/29791736/program-to-improve-private-early-education-pipe-a-case-study-of-a-systems-approach-for-scaling-quality-early-education-solutions
#9
Vikram Jain, Ahmed Irfan, Gauri Kirtane Vanikar
FSG is a mission-driven nonprofit organization supporting leaders in creating large-scale, lasting social change. A survey conducted by FSG in 2015 across 4407 low-income families in urban India showed that 95% of them send their children to preschools, a majority of choosing affordable private preschools (APSs), as parents perceive the quality of government schools to be poor. Parents use and value rote-based methods (e.g., reciting poems) to assess their children's learning in school; however, these methods fail to measure conceptual understanding...
May 2018: Annals of the New York Academy of Sciences
https://www.readbyqxmd.com/read/29791463/recurrent-spatio-temporal-modeling-of-check-ins-in-location-based-social-networks
#10
Ali Zarezade, Sina Jafarzadeh, Hamid R Rabiee
Social networks are getting closer to our real physical world. People share the exact location and time of their check-ins and are influenced by their friends. Modeling the spatio-temporal behavior of users in social networks is of great importance for predicting the future behavior of users, controlling the users' movements, and finding the latent influence network. It is observed that users have periodic patterns in their movements. Also, they are influenced by the locations that their close friends recently visited...
2018: PloS One
https://www.readbyqxmd.com/read/29791430/ex-vivos-models-to-teaching-therapeutic-endoscopic-ultrasound-t-eus
#11
Everson L A Artifon, Spencer Cheng, Thaisa Nakadomari, Leandro Kashiwagi, Jose Celso Ardengh, Emilio Belmonte, Jose P Otoch
BACKGROUND: Endoscopic ultrasound training has a learning curve greater than the other endoscopic therapeutic techniques. One of the preclinical teaching methods is the use of ex vivo porcine models. AIM: To describe five ex vivo porcine models for training in therapeutic echoendoscopic procedures. MATERIALS AND METHODS: Using porcine digestive tract containing esophagus, stomach, duodenum, spleen, liver and gallbladder, five models for therapeutic echoendoscopy training were described...
January 2018: Revista de Gastroenterología del Perú: órgano Oficial de la Sociedad de Gastroenterología del Perú
https://www.readbyqxmd.com/read/29791353/deep-learning-generated-holography
#12
Ryoichi Horisaki, Ryosuke Takagi, Jun Tanida
We present a method for computer-generated holography based on deep learning. The inverse process of light propagation is regressed with a number of computationally generated speckle data sets. This method enables noniterative calculation of computer-generated holograms (CGHs). The proposed method was experimentally verified with a phase-only CGH.
May 10, 2018: Applied Optics
https://www.readbyqxmd.com/read/29791349/polarimetric-learning-a-siamese-approach-to-learning-distance-metrics-of-algal-mueller-matrix-images
#13
Xianpeng Li, Ran Liao, Hui Ma, Priscilla T Y Leung, Meng Yan
Polarimetric measurements are becoming increasingly accurate and fast to perform in modern applications. However, analysis on the polarimetric data usually suffers from its high-dimensional nature spatially, temporally, or spectrally. This paper associates polarimetric techniques with metric learning algorithms, namely, polarimetric learning, by introducing a distance metric learning method called Siamese network that aims to learn good distance metrics of algal Mueller matrix images in low-dimensional feature spaces...
May 10, 2018: Applied Optics
https://www.readbyqxmd.com/read/29791297/late-positive-component-event-related-potential-amplitude-predicts-long-term-classroom-based-learning
#14
Katherine W Turk, Ala'a A Elshaar, Rebecca G Deason, Nadine C Heyworth, Corrine Nagle, Bruno Frustace, Sean Flannery, Ann Zumwalt, Andrew E Budson
It is difficult to predict whether newly learned information will be retrievable in the future. A biomarker of long-lasting learning, capable of predicting an individual's future ability to retrieve a particular memory, could positively influence teaching and educational methods. Event-related potentials (ERPs) were investigated as a potential biomarker of long-lasting learning. Prior ERP studies have supported a dual-process model of recognition memory that categorizes recollection and familiarity as distinct memorial processes with distinct ERP correlates...
May 23, 2018: Journal of Cognitive Neuroscience
https://www.readbyqxmd.com/read/29791153/a-probabilistic-framework-for-constructing-temporal-relations-in-replica-exchange-molecular-trajectories
#15
Aditya Chattopadhyay, Min Zheng, Mark Paul Waller, U Deva Priyakumar
Knowledge of the structure and dynamics of biomolecules is essential for elucidating the underlying mechanisms of biological processes. Given the stochastic nature of many biological processes, like protein unfolding, it's almost impossible that two independent simulations will generate the exact same sequence of events, which makes direct analysis of simulations difficult. Statistical models like Markov Chains, transition networks etc. help in shedding some light on the mechanistic nature of such processes by predicting long-time dynamics of these systems from short simulations...
May 23, 2018: Journal of Chemical Theory and Computation
https://www.readbyqxmd.com/read/29791132/ptml-model-of-chembl-data-for-dopamine-targets-docking-synthesis-and-assay-of-new-plg-peptidomimetics
#16
Joana Ferreira da Costa, David Silva, Olga Caamaño, José M Brea, Maria Isabel Loza, Cristian R Munteanu, Alejandro Pazos, Xerardo García-Mera, Humbert González-Díaz
Predicting Drug-Protein Interactions (DPIs) for target proteins involved in Dopamine pathways is very important goal in medicinal chemistry. We can tackle this problem using Molecular Docking or Machine Learning (ML) models for one specific protein. Unfortunately, these models fail to account for large and complex Big Data sets of preclinical assays reported in public databases. This includes multiple conditions of assay like different experimental parameters, biological assays, target proteins, cell lines, organism of the target, organism of assay, etc...
May 23, 2018: ACS Chemical Neuroscience
https://www.readbyqxmd.com/read/29790960/complexcontact-a-web-server-for-inter-protein-contact-prediction-using-deep-learning
#17
Hong Zeng, Sheng Wang, Tianming Zhou, Feifeng Zhao, Xiufeng Li, Qing Wu, Jinbo Xu
ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image...
May 22, 2018: Nucleic Acids Research
https://www.readbyqxmd.com/read/29790839/how-to-monitor-the-breathing-of-laboratory-rodents-a-review-of-the-current-methods
#18
Julien Grimaud, Venkatesh N Murthy
Accurately measuring respiration in laboratory rodents is essential for many fields of research, including olfactory neuroscience, social behavior, learning and memory, and respiratory physiology. However, choosing the right technique to monitor respiration can be tricky, given the many criteria to take into account: reliability, precision, and invasiveness, to name a few. This review aims to assist experimenters in choosing the technique that will best fit their needs, by surveying the available tools, discussing their strengths and weaknesses, and offering suggestions for future improvements...
May 23, 2018: Journal of Neurophysiology
https://www.readbyqxmd.com/read/29790652/preparation-for-making-clinical-referrals
#19
Shaun P Qureshi, Katharine Rankin, Neill Storrar, Michael Freeman
BACKGROUND: The application of prior learning within medical curricula to real patient care is challenging. Clinical assistantships support UK medical students making the transition to postgraduate practice as doctors. This paper describes a method of teaching clinical referrals: the process of clinicians contacting colleagues for advice or services. The skills required are key to medical practice, and students should be supported to develop them in order to optimally benefit from their assistantships and prepare for practice...
May 23, 2018: Clinical Teacher
https://www.readbyqxmd.com/read/29790333/autonomous-scanning-probe-microscopy-in-situ-tip-conditioning-through-machine-learning
#20
Mohammad Rashidi, Robert A Wolkow
Atomic-scale characterization and manipulation with scanning probe microscopy rely upon the use of an atomically sharp probe. Here we present automated methods based on machine learning to automatically detect and recondition the quality of the probe of a scanning tunneling microscope. As a model system, we employ these techniques on the technologically relevant hydrogen-terminated silicon surface, training the network to recognize abnormalities in the appearance of surface dangling bonds. Of the machine learning methods tested, a convolutional neural network yielded the greatest accuracy, achieving a positive identification of degraded tips in 97% of the test cases...
May 23, 2018: ACS Nano
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