An AI-Driven Hybrid Framework for Intrusion Detection in IoT-Enabled E-Health

E-health has grown into a billion-dollar industry in the last decade. Its device's high throughput makes it an obvious target for cyberattacks, and these environments desperately need protection. In this scientific study, we presented an artificial intelligence (AI)-driven software-defined networking (SDN)-enabled intrusion detection system (IDS) to address increasing cyber threats in the E-health and internet of medical things (IoMT) environments. AI's success in various fields, including big data and intrusion detection systems, has prompted us to develop a flexible and cost-effective approach to protect such critical environments from cyberattacks. We present a hybrid model consisting of long short-term memory (LSTM) and gated recurrent unit (GRU). The proposed model was thoroughly evaluated using the publicly available CICDDoS2019 dataset and conventional evaluation measures. Furthermore, for proper validation, the proposed framework is compared with relevant classifiers, such as cu-GRU+ DNN and cu-BLSTM. We have further compared the proposed model with existing literature to prove its efficacy. Lastly, 10-fold cross-validation is also used to verify that our results are unbiased. The proposed approach has bypassed the current literature with extraordinary performance ramifications such as 99.01% accuracy, 99.04% precision, 98.80 percent recall, and 99.12% F1-score.

Intravenous Magnesium Sulphate: An Effective Therapy for Acute Severe Attack of Bronchial Asthma

Asthma is a global public health problem of 21st century and occurs due to complex interaction between genetic, behavioral and environmental factors. There are many drugs available for asthma and magnesium sulphate is given intravenously as an important adjunct therapy during the acute severe attack of asthma Objective: This study was panned to determine the effect of intravenous MgSO4 on pulmonary function test in acute severe attack of asthma. Methodology: A double blind placebo control study was conduced on about 132 asthmatics, which were aged between 18-60 years at Mayo Hospital Emergency with FEV1 ≤ 30% of the predicted value. Spirometry of all asthmatics (study and placebo groups) in the emergency department was performed by Spirolab III. Detailed history, general physical and systemic examination was conducted and all parameters were recorded. Modified Borg scale was used to determine the grade of dyspnea from 0-10. A total of 2ml of venous blood was taken to determine the serum magnesium levels. All patients were given Salbutamol inhalation and intravenous (I/V) Hydrocortisone. The study group was given 2gm of MgS04 intravenously in 20 minutes in a burette and Placebo group was given placebo (0.9% normal saline). Salbutamol inhalation was given at regular intervals and Spirometry was performed to determine lung functions. Results: The two groups (study group and placebo-treated group) were compared for FEV1 , FEV1 % predicted, PEFR and PEFR % predicted. There was 1.06 L increase in FEV1 in study group compared to 0.8 L in placebo group (p<0.05). The mean FEV1  in the study group was 47.75 % predicted as compared to 43.52% predicted in the placebo group. Similarly, PEFR also improved to 59.87% predicted in study group as compared to 48.7% predicted in the placebo treated patient (p= < 0.01). Conclusion: Intravenous MgSO4 causes improvement in lung functions during asthmatic attack.