Raghav Awasthi

Indraprastha Institute of Information Technology Delhi | IIITD · Computational Biology

Background: The infodemic we are experiencing with AI related publications in healthcare is unparalleled. The excitement and fear surrounding the adoption of rapidly evolving AI in healthcare applications pose a real challenge. Collaborative learning from published research is one of the best ways to understand the associated opportunities and chal...

Large language models (LLMs) have caught the imagination of researchers,developers and public in general the world over with their potential for transformation. Vast amounts of research and development resources are being provided to implement these models in all facets of life. Trained using billions of parameters, various measures of their accura...

COVID-19 pandemic has taught us many lessons, including the need to manage the exponential growth of knowledge, fast-paced development or modification of existing AI models, limited opportunities to conduct extensive validation studies, the need to understand bias and mitigate it, and lastly, implementation challenges related to AI in healthcare. W...

The effectiveness of a vaccine depends on vaccine uptake, which is influenced by various factors, including vaccine hesitancy. Vaccine hesitancy is a complex socio-behavioral issue, influenced by misinformation, distrust in healthcare providers and government organizations, fear of side effects, and cultural or religious beliefs. To address this pr...

The COVID-19 pandemic has highlighted the importance of monitoring mobility patterns and their impact on disease spread. This paper presents a methodology for developing effective pandemic surveillance systems by extracting scal- able graph features from mobility networks. We utilized Travel Patterns dataset to capture the daily number of individua...

The purpose of this review is to provide a comprehensive review of publications related to artificial intelligence (AI) applications in healthcare for the year 2022. With an exponentially increasing number of publications related to AI in healthcare,there is a need to have a curated,timely and data driven review. This year's review provides a compr...

Objective To discover global determinants of vaccine uptake behavior and to develop a generalizable machine learning model to predict the vulnerability of vaccine uptake behavior at the individual level. Methodology 23135 Respondents across the 23 countries were interviewed for the survey questionnaire, after preprocessing and cleaning data, we pe...

UNSTRUCTURED Objective: To discover global determinants of vaccine uptake behavior and to develop a generalizable machine learning model to predict the vulnerability of vaccine uptake behavior at the individual level. Methodology: 23135 Respondents across the 23 countries were interviewed for the survey questionnaire, after preprocessing and cleani...

Background: An ever increasing number of artificial intelligence (AI) models targeting healthcare applications are developed and published every day, but their use in real world decision making is limited. Beyond a quantitative assessment, it is important to have qualitative evaluation of the maturity of these publications with additional details r...

Importance Homelessness is a complex challenge with an estimated yearly economic burden of $6 billion in the United States. Mitigating homelessness requires an understanding of determinants of homelessness, their interaction with health factors, and quantification of impact. Objective To investigate the health, social and policy factors influencin...

BACKGROUND Making public health decisions is arduous due to the multifaceted complexity of data. The advancement of the reinforcement learning (RL) model provides a robust and explainable artificial intelligence framework for making decisions under uncertainty. OBJECTIVE This review paper summarizes the extensive research on the reinforcement mode...

Background Antimicrobial resistance(AMR) is the next big pandemic that threatens humanity. One Health approach to AMR requires quantification of interactions between health, demographic, socioeconomic, environmental, and geopolitical factors to design interventions. This study is focused on learning health system factors on Global AMR. Methods Thi...

A COVID-19 vaccine is our best bet for mitigating the ongoing onslaught of the pandemic. However, vaccine is also expected to be a limited resource. An optimal allocation strategy, especially in countries with access inequities and temporal separation of hot-spots, might be an effective way of halting the disease spread. We approach this problem by...

A review of over 4000+ articles published in 2021 related to artificial intelligence in healthcare.A BrainX Community exclusive, annual publication which has trends, specialist editorials and categorized references readily available to provide insights into related 2021 publications. Cite as: Mathur P, Mishra S, Awasthi R, Cywinski J, et al. (2022...

Question answering (QA) is one of the oldest research areas of AI and Compu- national Linguistics. QA has seen significant progress with the development of state-of-the-art models and benchmark datasets over the last few years. However, pre-trained QA models perform poorly for clinical QA tasks, presumably due to the complexity of electronic health...

BACKGROUND Evidence from peer-reviewed literature is the cornerstone for designing responses to global threats such as COVID-19. The collection of knowledge in publications needs to be distilled into evidence by leveraging natural language models and machine learning. OBJECTIVE We aim to show that new knowledge can be captured and tracked using th...

Background: Evidence from peer-reviewed literature is the cornerstone for designing responses to global threats such as COVID-19. In the massive and rapidly growing corpuses such as the COVID-19 publications, assimilating and synthesizing information is challenging. Leveraging a robust computational pipeline that evaluates multiple aspects such as...

Background: Antimicrobial resistance (AMR) is a complex multifactorial outcome of health, socio-economic and geopolitical factors. Therefore, tailored solutions for mitigation strategies could be more effective in dealing with this challenge. Knowledge-synthesis and actionable models learned upon large datasets are critical in order to diffuse the...

Background The COVID-19 pandemic has affected the health, economic, and social fabric of many nations worldwide. Identification of individual-level susceptibility factors may help people in identifying and managing their emotional, psychological, and social well-being. Objective This study is focused on learning a ranked list of factors that could...

Evidence from peer-reviewed literature is the cornerstone for designing responses to global threats such as COVID-19. The collection of knowledge and interpretation in publications needs to be distilled into evidence by leveraging natural language in ways beyond standard meta-analysis. Several studies have focused on mining evidence from text using...

Shock is a major killer in the ICU and machine learning based early predictions can potentially save lives. Generalization across age and geographical context is an unaddressed challenge. In this retrospective observational study, we built real-time shock prediction models generalized across age groups and continents. More than 1.5 million patient-...

Female sex workers(FSWs) are one of the most vulnerable and stigmatized groups in society. As a result, they often suffer from a lack of quality access to care. Grassroot organizations engaged in improving health services are often faced with the challenge of improving the effectiveness of interventions due to complex influences. This work combines...

BACKGROUND The COVID-19 pandemic has affected the health, economic, and social fabric of many nations worldwide. Identification of individual-level susceptibility factors may help people in identifying and managing their emotional, psychological, and social well-being. OBJECTIVE This study is focused on learning a ranked list of factors that could...

A COVID-19 vaccine is our best bet for mitigating the ongoing onslaught of the pandemic. However, vaccine is also expected to be a limited resource. An optimal allocation strategy, especially in countries with access inequities and a temporal separation of hot-spots might be an effective way of halting the disease spread. We approach this problem b...

More than 640,000 babies died of sepsis before they reach the age of one month in India in 2016. Despite a large number of government schemes aimed at reducing this rate, this number still remains high because of the complexity and interplay of factors involved. Finding an optimum policy and solutions to this problem needs learning from data. We in...

Importance COVID-19 pandemic has deeply affected the health, economic, and social fabric of nations. Identification of individual-level susceptibility factors may help people in identifying and managing their emotional, psychological, and social well-being. Objective This work is focused on learning a ranked list of factors that could indicate a p...

The relationship between meteorological factors such as temperature and humidity with COVID-19 incidence is still unclear after 6 months of the beginning of the pandemic. Some literature confirms the association of temperature with disease transmission while some oppose the same. This work intends to determine whether there is a causal association...

Importance: Insights into the country-wise differences in COVID-19 burden can impact the policies being developed to control disease spread. Objective: Present study evaluated the possible socio-economic and health related factors (and their temporal consistency) determining the disease burden of COVID-19. Design: A retrospective analysis for ident...

COVID-19 pandemic is an enigma with uncertainty caused by multiple biological and health systems factors. Although many models have been developed all around the world, transparent models that allow interacting with the assumptions will become more important as we test various strategies for lockdown, testing and social interventions and enable eff...

The flood of conflicting COVID-19 research has revealed that COVID-19 continues to be an enigma. Although more than 14,000 research articles on COVID-19 have been published with the disease taking a pandemic proportion, clinicians and researchers are struggling to distill knowledge for furthering clinical management and research. In this study, we...