Dhenuka Radhakrishnan

Scientist, CHEO Research Institute

Dr. Dhenuka Radhakrishnan is a pediatric respirologist and Director of the Asthma Program at the Children’s Hospital of Eastern Ontario. She is an Associate Professor in the Department of Pediatrics, University of Ottawa, and adjunct ICES Scientist. At the CHEO Research Institute, she is the Captain of the Data Driven Discoveries team and Academic Lead for Research Informatics.

Dr. Radhakrishnan’s research focus is to measure predictors of childhood respiratory morbidity and improve care delivery through the use of large data, and advanced analytics including artificial intelligence and machine learning.

Email Researcher Other Publications

Research Areas

Artificial Intelligence Cancer Health Data Emergency Department Research Asthma Global Health Curriculum Respiratory Sleep Apnea Bronchiolitis

Related News

  1. CHEO Hopes to Share World-First AI Algorithm to Diagnose Rare Disease

    13/11/2024

    CHEO Hopes to Share World-First AI Algorithm to Diagnose Rare Disease

  2. Using AI to predict which kids are at risk of repeat visits to the emergency for asthma and redirecting them to specialized care

    03/07/2024

    Using AI to predict which kids are at risk of repeat visits to the emergency for asthma and redirecting them to specialized care

  3. CHEO Research Institute appoints inaugural Chief Scientific Officer

    02/02/2024

    CHEO Research Institute appoints inaugural Chief Scientific Officer

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Research Projects

  1. Augmenting Insufficiently Accruing Oncology Clinical Trials Using Generative Models: Validation Study

    03/03/2025

    Recruiting a sufficient number of patients for clinical trials is challenging [1], and the inability to recruit participants is the cause of failure for many clinical trials [2]. Approximately, 25% of clinical trials are discontinued before completion [3], with insufficient recruitment being the most frequent reason in 31% of the cases [4]. For adult cancer trials, between 20% and 50% fail to complete or were unable to reach recruitment goals [5-9]. This has been exacerbated by the recent pandemic where many trials experienced a considerable reduction in recruitment rates [10-13], which has continued after the pandemic [12]. While poor accrual is a problem in all trials, it is a greater problem in government (ie, academic) sponsored trials [14,15]. When a study is unable to recruit a sufficient number of patients, the study can be stopped, and the relevant analyses are performed on the available data. However, not reaching accrual targets results in underpowered analyses, and the smaller sample sizes increase the risk of unstable parameter estimates.

  2. Emergency department visit count: a practical tool to predict asthma hospitalization in children

    01/06/2019

    We identified 2669 patients with 3300 asthma ED visits. ED visit count was an independent predictor of future hospitalization risk (p < 0.001), demonstrating a dose-dependent response.

  3. Generational Patterns of Asthma Incidence among Immigrants to Canada over Two Decades. A Population-based Cohort Study

    01/03/2018

    Incidence of asthma was compared between immigrants from different regions of the world and long-term Ontario residents and their children, with the aim of providing further insight into the influence of environmental exposures on the development of asthma.