The Experts below are selected from a list of 37239 Experts worldwide ranked by ideXlab platform
Jason Phua - One of the best experts on this subject based on the ideXlab platform.
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lung ultrasound training curriculum implementation and Learning Trajectory among respiratory therapists
Intensive Care Medicine, 2016Co-Authors: Kay Choong See, Venetia Ong, Jason Phua, S H Wong, R Leanda, J Santos, Juvel TaculodAbstract:Guidelines recommend teaching of lung ultrasound for critical care, though little information exists on how much training is required for independent practice, especially for non-physician trainees. We thus aimed to elucidate a threshold number of cases above which competency for independent practice may be attained for respiratory therapists (RTs). We conducted a prospective audit of lung ultrasound training between July 2014 and April 2015 in our 20-bed medical intensive care unit. Following theoretical instruction and self-Learning, trainees acquired images from 12 lung zones under direct supervision and classified images into six patterns. Assistance during image acquisition and correct interpretation of ultrasound images were recorded. Eleven ultrasound-naive RTs scanned an average of 15 patients each (170 patients in total). Among supervisor-adjudicated lung ultrasound findings, 35.5 % were abnormal. Blinded verification of the adjudicated findings was done for the first 92 patients (1104 images), with an agreement of 95.4 %. As RTs scanned more patients, there was a significant decrease in the proportion of images requiring supervisor assistance (Cuzick’s P < 0.001), and a significant increase in the proportion of correctly identified images (Cuzick’s P = 0.008). After trainees performed at least ten scans, less than 2 % of images required assistance with acquisition and less than 5 % were wrongly interpreted. Our training method allowed RTs to independently perform lung ultrasound after at least ten directly supervised scans. Given that RTs are likely to have less ultrasound knowledge and less clinical know-how compared to physicians, we believe that the same threshold number of scans may be also safely applied to the latter.
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lung ultrasound training curriculum implementation and Learning Trajectory among respiratory therapists
Intensive Care Medicine, 2016Co-Authors: Kay Choong See, Venetia Ong, Jason Phua, S H Wong, R Leanda, J Santos, Juvel TaculodAbstract:Purpose Guidelines recommend teaching of lung ultrasound for critical care, though little information exists on how much training is required for independent practice, especially for non-physician trainees. We thus aimed to elucidate a threshold number of cases above which competency for independent practice may be attained for respiratory therapists (RTs).
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basic critical care echocardiography by pulmonary fellows Learning Trajectory and prognostic impact using a minimally resourced training model
Critical Care Medicine, 2014Co-Authors: Kay Choong See, Venetia Ong, Rou An Tan, Jason PhuaAbstract:Objectives:The spread of basic critical care echocardiography may be limited by training resources. Another barrier is the lack of information about the Learning Trajectory and prognostic impact of individual basic critical care echocardiography domains like acute cor pulmonale determination and lef
Kay Choong See - One of the best experts on this subject based on the ideXlab platform.
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lung ultrasound training curriculum implementation and Learning Trajectory among respiratory therapists
Intensive Care Medicine, 2016Co-Authors: Kay Choong See, Venetia Ong, Jason Phua, S H Wong, R Leanda, J Santos, Juvel TaculodAbstract:Guidelines recommend teaching of lung ultrasound for critical care, though little information exists on how much training is required for independent practice, especially for non-physician trainees. We thus aimed to elucidate a threshold number of cases above which competency for independent practice may be attained for respiratory therapists (RTs). We conducted a prospective audit of lung ultrasound training between July 2014 and April 2015 in our 20-bed medical intensive care unit. Following theoretical instruction and self-Learning, trainees acquired images from 12 lung zones under direct supervision and classified images into six patterns. Assistance during image acquisition and correct interpretation of ultrasound images were recorded. Eleven ultrasound-naive RTs scanned an average of 15 patients each (170 patients in total). Among supervisor-adjudicated lung ultrasound findings, 35.5 % were abnormal. Blinded verification of the adjudicated findings was done for the first 92 patients (1104 images), with an agreement of 95.4 %. As RTs scanned more patients, there was a significant decrease in the proportion of images requiring supervisor assistance (Cuzick’s P < 0.001), and a significant increase in the proportion of correctly identified images (Cuzick’s P = 0.008). After trainees performed at least ten scans, less than 2 % of images required assistance with acquisition and less than 5 % were wrongly interpreted. Our training method allowed RTs to independently perform lung ultrasound after at least ten directly supervised scans. Given that RTs are likely to have less ultrasound knowledge and less clinical know-how compared to physicians, we believe that the same threshold number of scans may be also safely applied to the latter.
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lung ultrasound training curriculum implementation and Learning Trajectory among respiratory therapists
Intensive Care Medicine, 2016Co-Authors: Kay Choong See, Venetia Ong, Jason Phua, S H Wong, R Leanda, J Santos, Juvel TaculodAbstract:Purpose Guidelines recommend teaching of lung ultrasound for critical care, though little information exists on how much training is required for independent practice, especially for non-physician trainees. We thus aimed to elucidate a threshold number of cases above which competency for independent practice may be attained for respiratory therapists (RTs).
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basic critical care echocardiography by pulmonary fellows Learning Trajectory and prognostic impact using a minimally resourced training model
Critical Care Medicine, 2014Co-Authors: Kay Choong See, Venetia Ong, Rou An Tan, Jason PhuaAbstract:Objectives:The spread of basic critical care echocardiography may be limited by training resources. Another barrier is the lack of information about the Learning Trajectory and prognostic impact of individual basic critical care echocardiography domains like acute cor pulmonale determination and lef
Venetia Ong - One of the best experts on this subject based on the ideXlab platform.
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lung ultrasound training curriculum implementation and Learning Trajectory among respiratory therapists
Intensive Care Medicine, 2016Co-Authors: Kay Choong See, Venetia Ong, Jason Phua, S H Wong, R Leanda, J Santos, Juvel TaculodAbstract:Guidelines recommend teaching of lung ultrasound for critical care, though little information exists on how much training is required for independent practice, especially for non-physician trainees. We thus aimed to elucidate a threshold number of cases above which competency for independent practice may be attained for respiratory therapists (RTs). We conducted a prospective audit of lung ultrasound training between July 2014 and April 2015 in our 20-bed medical intensive care unit. Following theoretical instruction and self-Learning, trainees acquired images from 12 lung zones under direct supervision and classified images into six patterns. Assistance during image acquisition and correct interpretation of ultrasound images were recorded. Eleven ultrasound-naive RTs scanned an average of 15 patients each (170 patients in total). Among supervisor-adjudicated lung ultrasound findings, 35.5 % were abnormal. Blinded verification of the adjudicated findings was done for the first 92 patients (1104 images), with an agreement of 95.4 %. As RTs scanned more patients, there was a significant decrease in the proportion of images requiring supervisor assistance (Cuzick’s P < 0.001), and a significant increase in the proportion of correctly identified images (Cuzick’s P = 0.008). After trainees performed at least ten scans, less than 2 % of images required assistance with acquisition and less than 5 % were wrongly interpreted. Our training method allowed RTs to independently perform lung ultrasound after at least ten directly supervised scans. Given that RTs are likely to have less ultrasound knowledge and less clinical know-how compared to physicians, we believe that the same threshold number of scans may be also safely applied to the latter.
-
lung ultrasound training curriculum implementation and Learning Trajectory among respiratory therapists
Intensive Care Medicine, 2016Co-Authors: Kay Choong See, Venetia Ong, Jason Phua, S H Wong, R Leanda, J Santos, Juvel TaculodAbstract:Purpose Guidelines recommend teaching of lung ultrasound for critical care, though little information exists on how much training is required for independent practice, especially for non-physician trainees. We thus aimed to elucidate a threshold number of cases above which competency for independent practice may be attained for respiratory therapists (RTs).
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basic critical care echocardiography by pulmonary fellows Learning Trajectory and prognostic impact using a minimally resourced training model
Critical Care Medicine, 2014Co-Authors: Kay Choong See, Venetia Ong, Rou An Tan, Jason PhuaAbstract:Objectives:The spread of basic critical care echocardiography may be limited by training resources. Another barrier is the lack of information about the Learning Trajectory and prognostic impact of individual basic critical care echocardiography domains like acute cor pulmonale determination and lef
P. J. Edwards - One of the best experts on this subject based on the ideXlab platform.
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analogue synaptic noise implications and Learning improvements
International Journal of Neural Systems, 1993Co-Authors: P. J. Edwards, Alan F. MurrayAbstract:We analyse the effects of analogue noise on the synaptic arithmetic during multilayer perceptron training by expanding the cost function to include noise-mediated penalty terms. Predictions are made in the light of these calculations which suggest that fault tolerance, generalisation ability and Learning Trajectory should be improved by such noise-injection. Extensive simulation experiments on two distinct classification problems substantiate the claims. The results appear to be perfectly general for all training schemes where weights are adjusted incrementally, and have wide-ranging implications for all applications, particularly those involving "inaccurate" analogue neural VLSI.
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Synaptic weight noise during multilayer perceptron training: fault tolerance and training improvements
IEEE transactions on neural networks, 1993Co-Authors: Alan F. Murray, P. J. EdwardsAbstract:The authors develop a mathematical model of the effects of synaptic arithmetic noise in multilayer perceptron training. Predictions are made regarding enhanced fault-tolerance and generalization ability and improved Learning Trajectory. These predictions are subsequently verified by simulation. The results are perfectly general and have profound implications for the accuracy requirements in multilayer perceptron (MLP) training, particularly in the analog domain. >
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synaptic weight noise during mlp Learning enhances fault tolerance generalization and Learning Trajectory
Neural Information Processing Systems, 1992Co-Authors: Alan F. Murray, P. J. EdwardsAbstract:We analyse the effects of analog noise on the synaptic arithmetic during MultiLayer Perceptron training, by expanding the cost function to include noise-mediated penalty terms. Predictions are made in the light of these calculations which suggest that fault tolerance, generalisation ability and Learning Trajectory should be improved by such noise-injection. Extensive simulation experiments on two distinct classification problems substantiate the claims. The results appear to be perfectly general for all training schemes where weights are adjusted incrementally, and have wide-ranging implications for all applications, particularly those involving "inaccurate" analog neural VLSI.
Alan F. Murray - One of the best experts on this subject based on the ideXlab platform.
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analogue synaptic noise implications and Learning improvements
International Journal of Neural Systems, 1993Co-Authors: P. J. Edwards, Alan F. MurrayAbstract:We analyse the effects of analogue noise on the synaptic arithmetic during multilayer perceptron training by expanding the cost function to include noise-mediated penalty terms. Predictions are made in the light of these calculations which suggest that fault tolerance, generalisation ability and Learning Trajectory should be improved by such noise-injection. Extensive simulation experiments on two distinct classification problems substantiate the claims. The results appear to be perfectly general for all training schemes where weights are adjusted incrementally, and have wide-ranging implications for all applications, particularly those involving "inaccurate" analogue neural VLSI.
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Synaptic weight noise during multilayer perceptron training: fault tolerance and training improvements
IEEE transactions on neural networks, 1993Co-Authors: Alan F. Murray, P. J. EdwardsAbstract:The authors develop a mathematical model of the effects of synaptic arithmetic noise in multilayer perceptron training. Predictions are made regarding enhanced fault-tolerance and generalization ability and improved Learning Trajectory. These predictions are subsequently verified by simulation. The results are perfectly general and have profound implications for the accuracy requirements in multilayer perceptron (MLP) training, particularly in the analog domain. >
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synaptic weight noise during mlp Learning enhances fault tolerance generalization and Learning Trajectory
Neural Information Processing Systems, 1992Co-Authors: Alan F. Murray, P. J. EdwardsAbstract:We analyse the effects of analog noise on the synaptic arithmetic during MultiLayer Perceptron training, by expanding the cost function to include noise-mediated penalty terms. Predictions are made in the light of these calculations which suggest that fault tolerance, generalisation ability and Learning Trajectory should be improved by such noise-injection. Extensive simulation experiments on two distinct classification problems substantiate the claims. The results appear to be perfectly general for all training schemes where weights are adjusted incrementally, and have wide-ranging implications for all applications, particularly those involving "inaccurate" analog neural VLSI.