Faculty Opinions recommendation of The Video Classification of Intubation (VCI) score: a new description tool for tracheal intubation using videolaryngoscopy: A pilot study.

Author(s):  
Andrew Smith ◽  
Jan Hansel
2022 ◽  
Vol 39 (2) ◽  
pp. 183-184
Author(s):  
Rajinder Singh Chaggar ◽  
Sneh Vinu Shah ◽  
Michael Berry ◽  
Rajan Saini ◽  
Sanooj Soni ◽  
...  

2021 ◽  
Vol 38 (3) ◽  
pp. 324-326
Author(s):  
Rajinder Singh Chaggar ◽  
Sneh Vinu Shah ◽  
Michael Berry ◽  
Rajan Saini ◽  
Sanooj Soni ◽  
...  

Author(s):  
Elgison da Luz dos Santos ◽  
Maria de Fátima Fernandes Vara ◽  
Maira Ranciaro ◽  
Gustavo Tanaka Zelaga ◽  
Amanda Mayara Pereira Gomes ◽  
...  
Keyword(s):  

Author(s):  
Hehe Fan ◽  
Zhongwen Xu ◽  
Linchao Zhu ◽  
Chenggang Yan ◽  
Jianjun Ge ◽  
...  

We aim to significantly reduce the computational cost for classification of temporally untrimmed videos while retaining similar accuracy. Existing video classification methods sample frames with a predefined frequency over entire video. Differently, we propose an end-to-end deep reinforcement approach which enables an agent to classify videos by watching a very small portion of frames like what we do. We make two main contributions. First, information is not equally distributed in video frames along time. An agent needs to watch more carefully when a clip is informative and skip the frames if they are redundant or irrelevant. The proposed approach enables the agent to adapt sampling rate to video content and skip most of the frames without the loss of information. Second, in order to have a confident decision, the number of frames that should be watched by an agent varies greatly from one video to another. We incorporate an adaptive stop network to measure confidence score and generate timely trigger to stop the agent watching videos, which improves efficiency without loss of accuracy. Our approach reduces the computational cost significantly for the large-scale YouTube-8M dataset, while the accuracy remains the same.


Endoscopy ◽  
2010 ◽  
Vol 42 (03) ◽  
pp. 203-207 ◽  
Author(s):  
J. Tischendorf ◽  
S. Gross ◽  
R. Winograd ◽  
H. Hecker ◽  
R. Auer ◽  
...  

2020 ◽  
Vol 9 (9) ◽  
pp. 2765
Author(s):  
Yazi Al’joboori ◽  
Sarah J. Massey ◽  
Sarah L. Knight ◽  
Nick de N. Donaldson ◽  
Lynsey D. Duffell

Spinal cord stimulation may enable recovery of volitional motor control in people with chronic Spinal Cord Injury (SCI). In this study we explored the effects of adding SCS, applied transcutaneously (tSCS) at vertebral levels T10/11, to a sit-to-stand training intervention in people with motor complete and incomplete SCI. Nine people with chronic SCI (six motor complete; three motor incomplete) participated in an 8-week intervention, incorporating three training sessions per week. Participants received either tSCS combined with sit-to-stand training (STIM) or sit-to-stand training alone (NON-STIM). Outcome measures were carried out before and after the intervention. Seven participants completed the intervention (STIM N = 5; NON-STIM N = 2). Post training, improvements in International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) motor scores were noted in three STIM participants (range 1.0–7.0), with no change in NON-STIM participants. Recovery of volitional lower limb muscle activity and/or movement (with tSCS off) was noted in three STIM participants. Unassisted standing was not achieved in any participant, although standing with minimal assistance was achieved in one STIM participant. This pilot study has shown that the recruitment of participants, intervention and outcome measures were all feasible in this study design. However, some modifications are recommended for a larger trial.


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