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Training performance modeling

Oren Schwartz, Boris Kanevsky, M A J Sergey Kutikov, Cara H Olsen, Israel Dudkiewicz
Introduction: Attrition from training is associated with substantial financial and personnel loss. There is a plethora of medical literature and research of attrition rates related to initial/phase 1 training (basic combat training); however, the analysis of second phase training (commanders training, consisting of schools that qualify junior commanders and officers for infantry and non-infantry combat units) is limited. The purpose of this study is to perform a comprehensive survey regarding to medical attrition from commanders training in the IDF (Israeli Defense Forces) in order to present the commanders of the IDF a detailed situation report that will serve as an evidence-based platform for future policy planning and implementation...
March 14, 2018: Military Medicine
Shanon Seger, Manuel Stritt, Enrico Vezzali, Oliver Nayler, Patrick Hess, Peter M A Groenen, Anna K Stalder
Intratracheal administration of bleomycin induces fibrosis in the lung, which is mainly assessed by histopathological grading that is subjective. Current literature highlights the need of reproducible and quantitative pulmonary fibrosis analysis. If some quantitative studies looked at fibrosis parameters separately, none of them quantitatively assessed both aspects: lung tissue remodeling and collagenization. To ensure reliable quantification, support vector machine learning was used on digitalized images to design a fully automated method that analyzes two important aspects of lung fibrosis: (i) areas having substantial tissue remodeling with appearance of dense fibrotic masses and (ii) collagen deposition...
2018: PloS One
P Stefan, M Pfandler, P Wucherer, S Habert, J Fürmetz, S Weidert, E Euler, U Eck, M Lazarovici, M Weigl, N Navab
Surgical simulators are being increasingly used as an attractive alternative to clinical training in addition to conventional animal models and human specimens. Typically, surgical simulation technology is designed for the purpose of teaching technical surgical skills (so-called task trainers). Simulator training in surgery is therefore in general limited to the individual training of the surgeon and disregards the participation of the rest of the surgical team. The objective of the project Assessment and Training of Medical Experts based on Objective Standards (ATMEOS) is to develop an immersive simulated operating room environment that enables the training and assessment of multidisciplinary surgical teams under various conditions...
March 15, 2018: Der Unfallchirurg
Bo-Lun Zhao, Wen-Tao Li, Xiao-Hua Zhou, Su-Qian Wu, Hong-Shi Cao, Zhu-Ren Bao, Li-Bin An
The purpose of the present study was to establish an effective robotic assistive stepping pattern of body-weight-supported treadmill training based on a rat spinal cord injury (SCI) model and assess the effect by comparing this with another frequently used assistive stepping pattern. The recorded stepping patterns of both hind limbs of trained intact rats were edited to establish a 30-sec playback normal rat stepping pattern (NRSP). Step features (step length, step height, step number and swing duration), BBB scores, latencies, and amplitudes of the transcranial electrical motor-evoked potentials (tceMEPs) and neurofilament 200 (NF200) expression in the spinal cord lesion area during and after 3 weeks of body-weight-supported treadmill training (BWSTT) were compared in rats with spinal contusion receiving NRSP assistance (NRSPA) and those that received manual assistance (MA)...
April 2018: Experimental and Therapeutic Medicine
Nathan H Schumaker, Allen Brookes
Context: Simulation models are increasingly used in both theoretical and applied studies to explore system responses to natural and anthropogenic forcing functions, develop defensible predictions of future conditions, challenge simplifying assumptions that facilitated past research, and to train students in scientific concepts and technology. Researcher's increased use of simulation models has created a demand for new platforms that balance performance, utility, and flexibility. Objectives: We describe HexSim, a powerful new spatially-explicit, individual-based modeling framework that will have applications spanning diverse landscape settings, species, stressors, and disciplines (e...
February 1, 2018: Landscape Ecology
Dezső Ribli, Anna Horváth, Zsuzsa Unger, Péter Pollner, István Csabai
In the last two decades, Computer Aided Detection (CAD) systems were developed to help radiologists analyse screening mammograms, however benefits of current CAD technologies appear to be contradictory, therefore they should be improved to be ultimately considered useful. Since 2012, deep convolutional neural networks (CNN) have been a tremendous success in image recognition, reaching human performance. These methods have greatly surpassed the traditional approaches, which are similar to currently used CAD solutions...
March 15, 2018: Scientific Reports
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
Worapan Kusakunniran, Qiang Wu, Panrasee Ritthipravat, Jian Zhang
(Background and Objective): The occurrence of hard exudates is one of the early signs of diabetic retinopathy which is one of the leading causes of the blindness. Many patients with diabetic retinopathy lose their vision because of the late detection of the disease. Thus, this paper is to propose a novel method of hard exudates segmentation in retinal images in an automatic way. (Methods): The existing methods are based on either supervised or unsupervised learning techniques. In addition, the learned segmentation models may often cause miss-detection and/or fault-detection of hard exudates, due to the lack of rich characteristics, the intra-variations, and the similarity with other components in the retinal image...
May 2018: Computer Methods and Programs in Biomedicine
Han Sun, Xiong Zhang, Yacong Zhao, Yu Zhang, Xuefei Zhong, Zhaowen Fan
The novel human-computer interface (HCI) using bioelectrical signals as input is a valuable tool to improve the lives of people with disabilities. In this paper, surface electromyography (sEMG) signals induced by four classes of wrist movements were acquired from four sites on the lower arm with our designed system. Forty-two features were extracted from the time, frequency and time-frequency domains. Optimal channels were determined from single-channel classification performance rank. The optimal-feature selection was according to a modified entropy criteria (EC) and Fisher discrimination (FD) criteria...
March 15, 2018: Sensors
Christine W St Laurent, Brittany Masteller, John Sirard
PURPOSE: The purpose of this pilot study was to assess the efficacy of a suspension-training movement program to improve muscular- and skill-related fitness and functional movement in children, compared with controls. METHODS: In total, 28 children [male: 46%; age: 9.3 (1.5) y; body mass index percentile: 68.6 (27.5)] were randomly assigned to intervention (n = 17) or control (n = 11) groups. The intervention group participated in a 6-week suspension-training movement program for two 1-hour sessions per week...
March 15, 2018: Pediatric Exercise Science
Ethan Leng, Benjamin Spilseth, Lin Zhang, Jin Jin, Joseph S Koopmeiners, Gregory J Metzger
PURPOSE: Computer-aided detection/diagnosis (CAD) of prostate cancer (PCa) on multipara-metric MRI (mpMRI) is an active area of research. In the literature, the performance of predictive models trained to detect PCa on mpMRI has typically been reported in terms of voxel-wise mea-sures such as sensitivity and specificity and/or area under the receiver operating curve (AUC).However, it is unclear whether models that score higher by these measures are actually superior.Here, we propose a novel method for lesion identification as well as novel measures that assess the quality of the detected lesions...
March 15, 2018: Medical Physics
Veronica T Rowe, Marsha Neville
Task-oriented training is a contemporary intervention based on behavioral neuroscience and recent models of motor learning. It can logically be guided by the theory of occupational adaptation. This report presents the perceptions of four participants who underwent task-oriented training at home (TOTE Home) for upper extremity hemiparesis following a stroke. Guided by principles of motor learning and the theory of occupational adaptation, a directed content analysis was used with field notes recorded during the TOTE Home...
March 1, 2018: OTJR: Occupation, Participation and Health
David Haro Alonso, Miles N Wernick, Yongyi Yang, Guido Germano, Daniel S Berman, Piotr Slomka
BACKGROUND: We developed machine-learning (ML) models to estimate a patient's risk of cardiac death based on adenosine myocardial perfusion SPECT (MPS) and associated clinical data, and compared their performance to baseline logistic regression (LR). We demonstrated an approach to visually convey the reasoning behind a patient's risk to provide insight to clinicians beyond that of a "black box." METHODS: We trained multiple models using 122 potential clinical predictors (features) for 8321 patients, including 551 cases of subsequent cardiac death...
March 14, 2018: Journal of Nuclear Cardiology: Official Publication of the American Society of Nuclear Cardiology
Wendy Kersemaekers, Silke Rupprecht, Marc Wittmann, Chris Tamdjidi, Pia Falke, Rogier Donders, Anne Speckens, Niko Kohls
Background: Mindfulness trainings are increasingly offered in workplace environments in order to improve health and productivity. Whilst promising, there is limited research on the effectiveness of mindfulness interventions in workplace settings. Objective: To examine the feasibility and effectiveness of a Workplace Mindfulness Training (WMT) in terms of burnout, psychological well-being, organizational and team climate, and performance. Methods: This is a preliminary field study in four companies. Self-report questionnaires were administered up to a month before, at start of, and right at the end of the WMT, resulting in a pre-intervention and an intervention period...
2018: Frontiers in Psychology
Manuel Cappellari, Gianni Turcato, Stefano Forlivesi, Fabio Bagante, Gianfranco Cervellin, Giuseppe Lippi, Bruno Bonetti, Paolo Bovi, Danilo Toni
Background and purpose The nomogram is an important component of modern medical decision-making, which calculates the probability of an event entirely based on individual characteristics. We aimed to develop and validate a nomogram for individualized prediction of the probability of unfavorable outcome in intravenous thrombolysis-treated stroke patients included in the large multicenter Safe Implementation of Thrombolysis in Stroke-International Stroke Thrombolysis Register. Methods All patients registered in the Safe Implementation of Thrombolysis in Stroke-International Stroke Thrombolysis Register by 179 Italian centers between May 2001 and March 2016 were originally included...
January 1, 2018: International Journal of Stroke: Official Journal of the International Stroke Society
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
Simone de Campos Neitzke Winter, Rafael Michel de Macedo, Júlio Cesar Francisco, Paula Costa Santos, Ana Paula Sarraff Lopes, Leanderson Franco de Meira, Katherine A Teixeira de Carvalho, José Rocha Faria Neto, Ana Carolina Brandt de Macedo, Luiz César Guarita-Souza
BACKGROUND: Physical exercise should be part of the treatment of post-acute myocardial infarction (AMI) patients. OBJECTIVE: To evaluate the effects of two training prescription models (continuous x interval) and its impact on ventricular function in rats after AMI with normal ventricular function. METHODS: Forty Wistar rats were evaluated by echocardiography 21 days after the AMI. Those with LVEF = 50% (n = 29) were included in the study and randomized to control group (CG n = 10), continuous training group (CTG n = 9) or interval training group (ITG, n = 10)...
March 12, 2018: Arquivos Brasileiros de Cardiologia
Satoru Kudose, Masato Hoshi, Sanjay Jain, Joseph P Gaut
Acute kidney injury (AKI) is a significant cause of morbidity and mortality. Acute tubular injury is considered to be the early pathologic manifestation of AKI, however, the underlying pathology is complex, lacks standards for interpretation, and its relationship with AKI often is unclear or inconsistent. To clarify clinicopathologic correlations in AKI, we evaluated 32 histologic findings in 100 kidney biopsies from patients with AKI as a training set to correlate pathologic findings with clinical AKI grades...
March 13, 2018: American Journal of Surgical Pathology
Kevin A Day, Kristan A Leech, Ryan T Roemmich, Amy J Bastian
Acquiring new movements requires the capacity of the nervous system to remember previously experienced motor patterns. The phenomenon of faster re-learning after initial learning is termed 'savings'. Here we studied how savings of a novel walking pattern develops over several days of practice, and how this process can be accelerated. We introduced participants to a split-belt treadmill adaptation paradigm for 30 minutes for 5 consecutive days. After 5 training days, participants were able to produce near-perfect performance when switching between split and tied-belt environments...
March 14, 2018: Journal of Neurophysiology
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