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RISS 인기검색어
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- 저자 : ( Ishan Gupta ) (검색결과 2 건)
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Ayus Ishan,Natarajan Narayanan,Gupta Deepak 한국대기환경학회 2023 Asian Journal of Atmospheric Environment (AJAE) Vol.17 No.1
The adverse effect of air pollution has always been a problem for human health. The presence of a high level of air pollutants can cause severe illnesses such as emphysema, chronic obstructive pulmonary disease (COPD), or asthma. Air quality prediction helps us to undertake practical action plans for controlling air pollution. The Air Quality Index (AQI) reflects the degree of concentration of pollutants in a locality. The average AQI was calculated for the various cities in China to understand the annual trends. Furthermore, the air quality index has been predicted for ten major cities across China using five different deep learning techniques, namely, Recurrent Neural Network (RNN), Bidirectional Gated Recurrent unit (Bi-GRU), Bidirectional Long Short-Term Memory (BiLSTM), Convolutional Neural Network BiLSTM (CNN-BiLSTM), and Convolutional BiLSTM (Conv1D-BiLSTM). The performance of these models has been compared with a machine learning model, eXtreme Gradient Boosting (XGBoost) to discover the most efficient deep learning model. The results suggest that the machine learning model, XGBoost, outperforms the deep learning models. While Conv1D-BiLSTM and CNN-BiLSTM perform well among the deep learning models in the estimation of the air quality index (AQI), RNN and Bi-GRU are the least performing ones. Thus, both XGBoost and neural network models are capable of capturing the non-linearity present in the dataset with reliable accuracy.
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A systematic review of clinical and laboratory parameters of 3,000 COVID-19 cases
( Harsh Goel ),( Ishan Gupta ),( Mbbs-student ),( Meenakshi Mourya ),( Sukhdeep Gill ),( Anita Chopra ),( Amar Ranjan ),( Goura Kishor Rath ),( Pranay Tanwar ) 대한산부인과학회 2021 Obstetrics & Gynecology Science Vol.64 No.2
The coronavirus disease 2019 (COVID-19) has spread worldwide. It is still a pandemic and poses major health problem across the globe. In our review, clinical characteristics and laboratory parameters of COVID-19 patients were compiled systematically, with special reference to pregnant women in order to understand the disease course. An extensive literature search on various scientific databases for relevant manuscripts was conducted, which yielded 7 manuscripts for final analysis. The most common symptoms were fever (85%), cough (70.63%), chest tightness (37.36%), expectoration (33.27%), fatigue (32%), dyspnea (31.95%), and shortness of breath (31.19%), while hemoptysis (1.0%) was the least common. The associated comorbidities were hypertension (21.6%) and diabetes (10.0%). In terms of hematological parameters, lower total leukocyte counts were observed in 65% of cases and biochemical parameters, patients demonstrated elevated levels of albumin (53.72%), lactate dehydrogenase (45.71%), and natriuretic peptide (34.84%); however, total bilirubin was elevated in only 8% of cases. In the acute inflammatory cytokine profile, C-reactive protein (59.0%), tumor necrosis factor (58.0%), erythrocyte sedimentation rate (57.0%), interleukin-2 (IL- 2, 54.0%), and IL-6 (52.0%) levels were increased, while prolactin levels (6.5%) were minimally elevated. The recovery rate was approximately 41%, and mortality was about 6.5%. The study also concluded that the clinical symptoms of COVID-19 were similar among pregnant and non-pregnant women. There was no evidence of vertical transmission of COVID-19 infection. This review critically analyzed COVID-19 as a public health hazard in order to help policy makers, health care givers, and primary physicians to promote early diagnosis and prevention.
KCI
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