Media coverage/Awards

Media Coverage: 

First Study:

• A novel Bayesian Network analysis on the International Severe Asthma Registry (ISAR) has identified key clinical and biological pathways that contribute to the risk of future severe exacerbations in patients with severe asthma. Leveraging real-world data from over 6,800 biologic-naïve adults across 17 countries, the study—recently published in CHEST under the title “Prediction Pathway for Severe Asthma Exacerbations: A Bayesian Network Analysis”—provides significant insights into how complex clinical factors interact to influence exacerbation risk. 

• To learn more about the study, please read the full publication in CHEST, as well as the accompanying slide deck. 

Second Study:

• Pathways that predict severe asthma attacks (exacerbations) were found to be similar, with matching strength of prediction, in both clinical trials (Randomised Controlled Trials, RCTs) and real-world data (RWD) settings in the new International Severe Asthma Registry (ISAR) study “Interactive Pathways of Key Prognostic Factors in Severe Asthma: A Bayesian Network Comparison of Clinical Trials & Real-World Data”. 

• To learn more about the study, please read the full publication in CHEST, as well as the accompanying slide deck. 

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Awards:

• APSR Assembly Education Award (Link) for abstract presentation "Application of Bayesian network in investigating risk factors and treatment interactions in severe asthma patients" at the Asian Pacific Society of Respirology conference, November 16-19, 2023, Singapore. [APSR(2023)]

• Recipient of UGC Research Fellowship (Mar, 2018 - Mar, 2022) during Ph.D. at Banaras Hindu University.

Refereed for Journals: ​Computational Statistics (CoS) ; Healthcare (Healthcare); Symmetry (Symmetry); Mathematics (Mathematics); International Journal of Population Data Science (IJPDS)