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Gupta, Ruchi,Singh, Saru,Kaur, Sukhdeep,Singh, Kulvinder,Aujla, Kuljeet The Korean Pain Society 2014 The Korean Journal of Pain Vol.27 No.4
Background: Epidural steroid injections are an accepted procedure for the conservative management of chronic backache caused by lumbar disc pathology. The purpose of this study was to evaluate the epidurographic findings for the midline, transforaminal and parasagittal approaches in lumbar epidural steroid injections, and correlating them with the clinical improvement. Methods: Sixty chronic lower back pain patients with unilateral radiculitis from a herniated/degenerated disc were enrolled. After screening the patients according to the exclusion criteria and randomly allocating them to 3 groups of 20 patients, fluoroscopic contrast enhanced epidural steroids were injected via midline (group 1), transforaminal (group 2) and parasagittal interlaminar (group 3) approaches at the level of the pathology. The fluoroscopic patterns of the three groups were studied and correlated with the clinical improvement measured by the VAS over the next 3 months; any incidences of complications were recorded. Results: The transforaminal group presented better results in terms of VAS reduction than the midline and parasagittal approach groups (P < 0.05). The epidurography showed a better ventral spread for both the transforaminal (P < 0.001) and the paramedian approaches (P < 0.05), as compared to the midline approach. The nerve root filling was greater in the transforaminal group (P < 0.001) than in the other two groups. The ventral spread of the contrast agent was associated with improvement in the VAS score and this difference was statistically significant in group 1 (P < 0.05), and highly significant in groups 2 and 3 (P < 0.001). In all the groups, any complications observed were transient and minor. Conclusions: The midline and paramedian approaches are technically easier and statistically comparable, but clinically less efficacious than the transforaminal approach. The incidence of ventral spread and nerve root delineation show a definite correlation with clinical improvement. However, an longer follow-up period is advisable for a better evaluation of the actual outcom.
CoBiD-net: a tailored deep learning ensemble model for time series forecasting of covid-19
Shastri Sourabh,Singh Kuljeet,Deswal Monu,Kumar Sachin,Mansotra Vibhakar 대한공간정보학회 2022 Spatial Information Research Vol.30 No.2
The pandemic of novel coronavirus disease 2019 (Covid-19) has left the world to a standstill by creating a calamitous situation. To mitigate this devastating effect the inception of artificial intelligence into medical health care is mandatory. This study aims to present the educational perspective of Covid-19 and forecast the number of confirmed and death cases in the USA, India, and Brazil along with the discussion of endothelial dysfunction in epithelial cells and Angiotensin-Converting Enzyme 2 receptor (ACE2) with the Covid-19. Three different deep learning based experimental setups have been framed to forecast Covid-19. Models are (i) Bi-directional Long Short Term Memory (LSTM) (ii) Convolutional LSTM (iii) Proposed ensemble of Convolutional and Bi-directional LSTM network are known as CoBiD-Net ensemble. The educational perspective of Covid-19 has been given along with an architectural discussion of multi-organ failure due to intrusion of Covid-19 with the cell receptors of the human body. Different classification metrics have been calculated using all three models. Proposed CoBiD-Net ensemble model outperforms the other two models with respect to accuracy and mean absolute percentage error (MAPE). Using CoBiD-Net ensemble, accuracy for Covid-19 cases ranges from 98.10 to 99.13% with MAPE ranges from 0.87 to 1.90. This study will help the countries to know the severity of Covid-19 concerning education in the future along with forecasting of Covid-19 cases and human body interaction with the Covid-19 to make it the self-replicating phenomena.
CoBiD-net: a tailored deep learning ensemble model for time series forecasting of covid-19
Shastri Sourabh,Singh Kuljeet,Deswal Monu,Kumar Sachin,Mansotra Vibhakar 대한공간정보학회 2022 Spatial Information Research Vol.30 No.1
The pandemic of novel coronavirus disease 2019 (Covid-19) has left the world to a standstill by creating a calamitous situation. To mitigate this devastating effect the inception of artificial intelligence into medical health care is mandatory. This study aims to present the educational perspective of Covid-19 and forecast the number of confirmed and death cases in the USA, India, and Brazil along with the discussion of endothelial dysfunction in epithelial cells and Angiotensin-Converting Enzyme 2 receptor (ACE2) with the Covid-19. Three different deep learning based experimental setups have been framed to forecast Covid-19. Models are (i) Bi-directional Long Short Term Memory (LSTM) (ii) Convolutional LSTM (iii) Proposed ensemble of Convolutional and Bi-directional LSTM network are known as CoBiD-Net ensemble. The educational perspective of Covid-19 has been given along with an architectural discussion of multi-organ failure due to intrusion of Covid-19 with the cell receptors of the human body. Different classification metrics have been calculated using all three models. Proposed CoBiD-Net ensemble model outperforms the other two models with respect to accuracy and mean absolute percentage error (MAPE). Using CoBiD-Net ensemble, accuracy for Covid-19 cases ranges from 98.10 to 99.13% with MAPE ranges from 0.87 to 1.90. This study will help the countries to know the severity of Covid-19 concerning education in the future along with forecasting of Covid-19 cases and human body interaction with the Covid-19 to make it the self-replicating phenomena.
( Ruchi Gupta ),( Saru Singh ),( Sukhdeep Kaur ),( Kulvinder Singh ),( Kuljeet Aujla ) 대한통증학회 2014 The Korean Journal of Pain Vol.27 No.4
Background: Epidural steroid injections are an accepted procedure for the conservative management of chronic backache caused by lumbar disc pathology. The purpose of this study was to evaluate the epidurographic findings for the midline, transforaminal and parasagittal approaches in lumbar epidural steroid injections, and correlating them with the clinical improvement.Methods: Sixty chronic lower back pain patients with unilateral radiculitis from a herniated/degenerated disc were enrolled. After screening the patients according to the exclusion criteria and randomly allocating them to 3 groups of 20 patients, fluoroscopic contrast enhanced epidural steroids were injected via midline (group 1), transforaminal (group 2) and parasagittal interlaminar (group 3) approaches at the level of the pathology. The fluoroscopic patterns of the three groups were studied and correlated with the clinical improvement measured by the VAS over the next 3 months; any incidences of complications were recorded. Results: The transforaminal group presented better results in terms of VAS reduction than the midline and parasagittal approach groups (P < 0.05). The epidurography showed a better ventral spread for both the transforaminal (P < 0.001) and the paramedian approaches (P < 0.05), as compared to the midline approach. The nerve root filling was greater in the transforaminal group (P < 0.001) than in the other two groups. The ventral spread of the contrast agent was associated with improvement in the VAS score and this difference was statistically significant in group 1 (P < 0.05), and highly significant in groups 2 and 3 (P < 0.001). In all the groups, any complications observed were transient and minor. Conclusions: The midline and paramedian approaches are technically easier and statistically comparable, but clinically less efficacious than the transforaminal approach. The incidence of ventral spread and nerve root delineation show a definite correlation with clinical improvement. However, an longer follow-up period is advisable for a better evaluation of the actual outcom. (Korean J Pain 2014; 27: 353-359)