A Review of the Machine Learning Algorithms for Covid-19 Case Analysis.

The purpose of this article is to see how machine learning (ML) algorithms and applications are used in the COVID-19 inquiry and for other purposes. The available traditional methods for COVID-19 international epidemic prediction, researchers and authorities have given more attention to simple statistical and epidemiological methodologies. The inadequacy and absence of medical testing for diagnosing and identifying a solution is one of the key challenges in preventing the spread of COVID-19. A few statistical-based improvements are being strengthened to answer this challenge, resulting in a partial resolution up to a certain level. ML have advocated a wide range of intelligence-based approaches, frameworks, and equipment to cope with the issues of the medical industry. The application of inventive structure, such as ML and other in handling COVID-19 relevant outbreak difficulties, has been investigated in this article. The major goal of this article is to 1) Examining the impact of the data type and data nature, as well as obstacles in data processing for COVID-19. 2) Better grasp the importance of intelligent approaches like ML for the COVID-19 pandemic. 3) The development of improved ML algorithms and types of ML for COVID-19 prognosis. 4) Examining the effectiveness and influence of various strategies in COVID-19 pandemic. 5) To target on certain potential issues in COVID-19 diagnosis in order to motivate academics to innovate and expand their knowledge and research into additional COVID-19-affected industries.

Anti-asthmatic effect of Shirishadi compound through nasal spray actuation.

BACKGROUND: Increasing morbidity and mortality of Asthma placed it among the most dreaded diseases. Prediction says that asthma along with chronic obstructive pulmonary disease become third leading cause of death by the year 2020. Despite the availability of a wide range of antiasthmatic drugs, incidence of asthma is increasing alarmingly because the relief offered by these drugs is mainly symptomatic and short-lived. Moreover, their side effects are also quite distressing. Hence, a continuous search is needed to identify effective and safe remedies to treat bronchial asthma. AIMS: The present clinical study was conducted to evaluate the efficacy of Shirishadi Polyherbal compound (given through nebulizer in Aerosol form) in the management of acute and chronic uncomplicated Bronchial Asthma and to propose a novel and safer Ayurvedic treatment modality. METHODS AND MATERIALS: It is a randomized, open, control clinical trial in which the effect of the drug was compared with contemporary treatment and placebo medication (normal saline) in 60 adults with mild to moderate asthma. RESULTS: There was a (t>0.001) found in pulmonary function tests (including FEV1, FVC and PEFR)in the group treated with polyherbal drug. Improvement remain constant in consecutive follow-ups signifies that there is no reverse broncho-constriction after discontinuation of the drug. CONCLUSION: This study signifies that polyherbal drug - Shirishadi compound may prove beneficial future alternative remedy for asthma, and its effect is similar to that of modern contemporary drug when given through nasal route.

Evaluation of in vitro antioxidant capacity and reducing potential of polyherbal drug- Bharangyadi.

BACKGROUND: Present work was designed to investigate antioxidant activity of polyherbal formulation in search for new, safe and inexpensive antioxidant. Clerodendrum serratum, Hedychium spicatum and Inula racemosa, were extensively used in ayurvedic medicine and were investigated together in the form of polyherbal compound (Bharangyadi) for their antioxidant potential. MATERIALS AND METHODS: Hydroalcoholic extract was prepared from the above samples and was tested for total reducing power and in vitro antioxidant activity by ABTS(+) assay, Superoxide anion scavenging activity assay and lipid per-oxidation assay. RESULT: Reducing power shows dose depended increase in concentration maximum absorption of 0.677 ± 0.017 at 1000 µg/ml compared with standard Quercetin 0.856±0.020. ABTS(+) assay shows maximum inhibition of 64.2 ± 0.86 with EC50 675.31 ± 4.24. Superoxide free radical shows maximum scavenging activity of 62.45 ± 1.86 with EC50 774.70 ± 5.45. Anti-lipidperoxidation free radicals scavenge maximum absorption of 67.25± 1.89 with EC50 is 700.08 ± 6.81. Ascorbic acid was used as standard with IC50 value is 4.6 µg/ml. The result suggests polyherbal formulation to be a good potential for antioxidant activity. Oxidative stress results from imbalance between free radical-generation and radical scavenging systems. This will lead to tissue damage and oxidative stress. CONCLUSION: In conclusion, we strongly suggest that Polyherbal compounds are source of potential antioxidant for radical scavenging. The highly positive correlation of antiradical scavenging activity and total polyphenolic content in Polyherbal compounds indicates that polyphenols are important components which could be used for the free radical scavenging activity. Further study is needed for isolation and characterization of the active moiety responsible for biological activity and to treat in various stress condition.