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Operant learning

Lila R Gleitman, John C Trueswell
This article describes early stages in the acquisition of a first vocabulary by infants and young children. It distinguishes two major stages, the first of which operates by a stand-alone word-to-world pairing procedure and the second of which, using the evidence so acquired, builds a domain-specific syntax-sensitive structure-to-world pairing procedure. As we show, the first stage of learning is slow, restricted in character, and to some extent errorful, whereas the second procedure is determinative, rapid, and essentially errorless...
June 15, 2018: Topics in Cognitive Science
Santosh D Bhosale, Robert Moulder, Mikko S Venäläinen, Juhani S Koskinen, Niina Pitkänen, Markus T Juonala, Mika A P Kähönen, Terho J Lehtimäki, Jorma S A Viikari, Laura L Elo, David R Goodlett, Riitta Lahesmaa, Olli T Raitakari
To evaluate the presence of serum protein biomarkers associated with the early phases of formation of carotid atherosclerotic plaques, label-free quantitative proteomics analyses were made for serum samples collected as part of The Cardiovascular Risk in Young Finns Study. Samples from subjects who had an asymptomatic carotid artery plaque detected by ultrasound examination (N = 43, Age = 30-45 years) were compared with plaque free controls (N = 43) (matched for age, sex, body weight and systolic blood pressure)...
June 15, 2018: Scientific Reports
Jean L Wright, Arti Parekh, Byung-Han Rhieu, Valentina Opris, Annette Souranis, Amanda Choflet, Akila N Viswanathan, Theodore L DeWeese, Todd McNutt, Stephanie A Terezakis
PURPOSE: The optimal approach to managing incident learning system (ILS) reports remains unclear. Here, we describe our experience with prospective coding of events reported to the ILS with comparisons of risk scores on the basis of event type and process map location. METHODS AND MATERIALS: Reported events were coded by type, origin, and method of discovery. Events were given a risk priority number (RPN) and near-miss risk index (NMRI) score. We compared workflow versus near-miss events with respect to origin and detection in the process map and by risk scores...
May 8, 2018: Practical Radiation Oncology
Kazushige Kawai, Keisuke Hata, Toshiaki Tanaka, Takeshi Nishikawa, Kensuke Otani, Koji Murono, Kazuhito Sasaki, Manabu Kaneko, Shigenobu Emoto, Hiroaki Nozawa
OBJECTIVE: This study aimed to assess the learning curve of robotic rectal surgery, a procedure that has gained increasing focus in recent years because it is expected that the advanced devices used in this approach provide advantages resulting in a shorter learning curve than that of laparoscopic surgery. However, no studies have assessed the learning curve of robotic rectal surgery, especially when lateral lymph node dissection is required. DESIGN: This was a nonrandomized, retrospective study from a single institution...
June 12, 2018: Journal of Surgical Education
Joshua Parreco, Antonio Hidalgo, Jonathan J Parks, Robert Kozol, Rishi Rattan
BACKGROUND: Early identification of critically ill patients who will require prolonged mechanical ventilation (PMV) has proven to be difficult. The purpose of this study was to use machine learning to identify patients at risk for PMV and tracheostomy placement. MATERIALS AND METHODS: The Multiparameter Intelligent Monitoring in Intensive Care III database was queried for all intensive care unit (ICU) stays with mechanical ventilation. PMV was defined as ventilation >7 d...
August 2018: Journal of Surgical Research
Mai Oudah, Andreas Henschel
BACKGROUND: What is a healthy microbiome? The pursuit of this and many related questions, especially in light of the recently recognized microbial component in a wide range of diseases has sparked a surge in metagenomic studies. They are often not simply attributable to a single pathogen but rather are the result of complex ecological processes. Relatedly, the increasing DNA sequencing depth and number of samples in metagenomic case-control studies enabled the applicability of powerful statistical methods, e...
June 15, 2018: BMC Bioinformatics
Vincent Weidlich, Georg A Weidlich
Artifical Intelligence (AI) was reviewed with a focus on its potential applicability to radiation oncology. The improvement of process efficiencies and the prevention of errors were found to be the most significant contributions of AI to radiation oncology. It was found that the prevention of errors is most effective when data transfer processes were automated and operational decisions were based on logical or learned evaluations by the system. It was concluded that AI could greatly improve the efficiency and accuracy of radiation oncology operations...
April 13, 2018: Curēus
Arielle E Kanters, Sarah P Shubeck, Gurjit Sandhu, Caprice C Greenberg, Justin B Dimick
BACKGROUND: The quality of an operation depends on operative technique. There is very little evidence, however, regarding how surgeons arrive at their intraoperative decisions. The objective of this study was to determine the extent to which practicing surgeons participating in a coaching program justify their technical decisions based on their experience or based on evidence. METHODS: This qualitative study evaluated 10 pairs of surgeons participating in a video review coaching program in October 2015...
June 11, 2018: Surgery
Mohammed A Al-Masni, Mugahed A Al-Antari, Mun-Taek Choi, Seung-Moo Han, Tae-Seong Kim
BACKGROUND AND OBJECTIVE: Automatic segmentation of skin lesions in dermoscopy images is still a challenging task due to the large shape variations and indistinct boundaries of the lesions. Accurate segmentation of skin lesions is a key prerequisite step for any computer-aided diagnostic system to recognize skin melanoma. METHODS: In this paper, we propose a novel segmentation methodology via full resolution convolutional networks (FrCN). The proposed FrCN method directly learns the full resolution features of each individual pixel of the input data without the need for pre- or post-processing operations such as artifact removal, low contrast adjustment, or further enhancement of the segmented skin lesion boundaries...
August 2018: Computer Methods and Programs in Biomedicine
Giovanni Lucca França da Silva, Thales Levi Azevedo Valente, Aristófanes Corrêa Silva, Anselmo Cardoso de Paiva, Marcelo Gattass
BACKGROUND AND OBJECTIVE: Detection of lung nodules is critical in CAD systems; this is because of their similar contrast with other structures and low density, which result in the generation of numerous false positives (FPs). Therefore, this study proposes a methodology to reduce the FP number using a deep learning technique in conjunction with an evolutionary technique. METHOD: The particle swarm optimization (PSO) algorithm was used to optimize the network hyperparameters in the convolutional neural network (CNN) in order to enhance the network performance and eliminate the requirement of manual search...
August 2018: Computer Methods and Programs in Biomedicine
Egidio D'Angelo
The cerebellum is a central brain structure deeply integrated into major loops with the cerebral cortex, brainstem, and spinal cord. The cerebellum shows a complex regional organization consisting of modules with sagittal orientation. The cerebellum takes part in motor control and its lesions cause a movement incoordination syndrome called ataxia. Recent observations also imply involvement of the cerebellum in cognition and executive control, with an impact on pathologies like dyslexia and autism. The cerebellum operates as a forward controller learning to predict the precise timing of correlated events...
2018: Handbook of Clinical Neurology
Sebastian Olikira Baine, Alex Kakama, Moses Mugume
BACKGROUND: Kisiizi Hospital Health Insurance scheme started in 1996 to; improve access to health services, and provide a stable source of funding and reduce bad debts to Kisiizi hospital. Objectives of this study were; to describe Kisiizi Hospital Health Insurance scheme and to document lessons learned and implications for universal health coverage. METHODS: This was a descriptive cross-sectional study. Data from different sources were triangulated and thematically analysed...
June 15, 2018: BMC Health Services Research
Umberto Bracale, Giovanni Merola, Antonio Sciuto, Giuseppe Cavallaro, Jacopo Andreuccetti, Giusto Pignata
BACKGROUND: More than 20 million patients worldwide undergo groin hernia repair annually. Every year more than 800,000 inguinal hernia repairs are performed in the United States alone. Since the first report by Ger et al. in 1990, laparoscopic inguinal hernia repair has gained wide acceptance due to its many advantages with more than 20% of inguinal hernias treated by this approach. The aim of our study is to estimate the number of cases needed over the course of a trainee's learning curve period to achieve stabilization of operating time and intra and post-operative complication rates when performing laparoscopic transabdominal preperitoneal hernia repair (TAPP)...
June 14, 2018: Journal of Investigative Surgery: the Official Journal of the Academy of Surgical Research
Eleanor J Radford, Theo Fotis
Operating theatre scrub nurses (OTSNs) are not required to have undertaken a secondary or specialist post-registration theatre qualification to work in the operating theatre (OT) setting in the UK. From the systematic review there is only very limited literature or research in how technical scrub skills are acquired. This study explores the lived experiences of OTSNs learning technical scrub skills. The study employed the qualitative methodology of interpretative phenomenological analysis. Data was collected from six participating OTSNs using semi-structured interviews...
January 1, 2018: Journal of Perioperative Practice
Federico Landriel, Santiago Hem, Jorge Rasmussen, Eduardo Vecchi, Claudio Yampolsky
Objective: The aim of this study was to estimate the learning curve needed for correct placement of minimally invasive percutaneous pedicle screws (PPS). Introduction: PPS are the most common system used for instrumentation of spinal lesions that require stabilization. Methods: We retrospectively assessed the insertion of 422 PPS (T5 to S1) in 75 patients operated between 2013-2016 under two-dimensional fluoroscopic guidance. The surgeon 1 always placed the PPS on the right side and the surgeon 2 on the left side...
2018: Surgical Neurology International
Sonu Goel, Ajay M V Kumar, Arun Kumar Aggarwal, Rana J Singh, Pranay Lal, Ravinder Kumar, Madhu Gupta, Vishal Dogra, Deepti Gupta
Background: Several competing priorities with health and development sector currently deter research, and as a result of which evidence does not drive policy- or decision-making. There is limited operational research (OR) within the India's National Tobacco Control Programme, as it is in other middle- and low-income countries, primarily due to limited capacity and skills in undertaking OR and lack of dedicated funding. Few models of OR have been developed to meet the needs of different settings; however, they were found to be costly and time-consuming...
April 2018: Indian Journal of Community Medicine
Babak Ehteshami Bejnordi, Maeve Mullooly, Ruth M Pfeiffer, Shaoqi Fan, Pamela M Vacek, Donald L Weaver, Sally Herschorn, Louise A Brinton, Bram van Ginneken, Nico Karssemeijer, Andrew H Beck, Gretchen L Gierach, Jeroen A W M van der Laak, Mark E Sherman
The breast stromal microenvironment is a pivotal factor in breast cancer development, growth and metastases. Although pathologists often detect morphologic changes in stroma by light microscopy, visual classification of such changes is subjective and non-quantitative, limiting its diagnostic utility. To gain insights into stromal changes associated with breast cancer, we applied automated machine learning techniques to digital images of 2387 hematoxylin and eosin stained tissue sections of benign and malignant image-guided breast biopsies performed to investigate mammographic abnormalities among 882 patients, ages 40-65 years, that were enrolled in the Breast Radiology Evaluation and Study of Tissues (BREAST) Stamp Project...
June 13, 2018: Modern Pathology: An Official Journal of the United States and Canadian Academy of Pathology, Inc
Wei Chen, Jianbing Peng, Haoyuan Hong, Himan Shahabi, Biswajeet Pradhan, Junzhi Liu, A-Xing Zhu, Xiangjun Pei, Zhao Duan
The preparation of a landslide susceptibility map is considered to be the first step for landslide hazard mitigation and risk assessment. However, these maps are accepted as end products that can be used for land use planning. The main goal of this study is to assess and compare four advanced machine learning techniques, namely the Bayes' net (BN), radical basis function (RBF) classifier, logistic model tree (LMT), and random forest (RF) models, for landslide susceptibility modelling in Chongren County, China...
June 1, 2018: Science of the Total Environment
Lorena Simon-Vidal, Oihane García-Calvo, Uxue Oteo, Sonia Arrasate, Esther Lete, Nuria Sotomayor, Humbert González-Díaz
Machine Learning (ML) algorithms are gaining importance in the processing of chemical information and modelling of chemical reactivity problems. In this work, we have developed a PTML model combining Perturbation-Theory (PT) and ML algorithms for predicting the yield of a given reaction. For this purpose, we have selected Parham cyclization, which is a general and powerful tool for the synthesis of heterocyclic and carbocyclic compounds. This reaction has both structural (substitution pattern on the substrate, internal electrophile, ring size, etc...
June 13, 2018: Journal of Chemical Information and Modeling
Chang-Qin Huang, Shang-Ming Yang, Yan Pan, Han-Jiang Lai
Learning-based hashing is a leading approach of approximate nearest neighbor search for large-scale image retrieval. In this paper, we develop a deep supervised hashing method for multi-label image retrieval, in which we propose to learn a binary "mask" map that can identify the approximate locations of objects in an image, so that we use this binary "mask" map to obtain length-limited hash codes which mainly focus on an image's objects but ignore the background. The proposed deep architecture consists of four parts: 1) a convolutional sub-network to generate effective image features; 2) a binary "mask" sub-network to identify image objects' approximate locations; 3) a weighted average pooling operation based on the binary "mask" to obtain feature representations and hash codes that pay most attention to foreground objects but ignore the background; and 4) the combination of a triplet ranking loss designed to preserve relative similarities among images and a cross entropy loss defined on image labels...
September 2018: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
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